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abdulmanaam/distilroberta-base-clickbait-task1-20-epoch-post_title

abdulmanaam

--- license: apache-2.0 base_model: distilbert/distilroberta-base tags: - generated_from_trainer metrics: - accuracy model-index: - name: distilroberta-base-clickbait-task1-20-epoch-post_title results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # distilroberta-base-clickbait-task1-20-epoch-post_title This model is a fine-tuned version of [distilbert/distilroberta-base](https://huggingface.co/distilbert/distilroberta-base) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 2.5249 - Accuracy: 0.6975 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 20 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | No log | 1.0 | 200 | 0.7856 | 0.6475 | | No log | 2.0 | 400 | 0.7447 | 0.71 | | 0.7757 | 3.0 | 600 | 0.7684 | 0.6925 | | 0.7757 | 4.0 | 800 | 0.9055 | 0.705 | | 0.3775 | 5.0 | 1000 | 0.9552 | 0.715 | | 0.3775 | 6.0 | 1200 | 1.3111 | 0.69 | | 0.3775 | 7.0 | 1400 | 1.5227 | 0.715 | | 0.1375 | 8.0 | 1600 | 1.8561 | 0.6975 | | 0.1375 | 9.0 | 1800 | 1.9567 | 0.7 | | 0.0543 | 10.0 | 2000 | 2.2423 | 0.6875 | | 0.0543 | 11.0 | 2200 | 2.0781 | 0.695 | | 0.0543 | 12.0 | 2400 | 2.3912 | 0.6725 | | 0.0273 | 13.0 | 2600 | 2.3334 | 0.6975 | | 0.0273 | 14.0 | 2800 | 2.3251 | 0.715 | | 0.0144 | 15.0 | 3000 | 2.5461 | 0.6875 | | 0.0144 | 16.0 | 3200 | 2.5073 | 0.71 | | 0.0144 | 17.0 | 3400 | 2.4647 | 0.6925 | | 0.0079 | 18.0 | 3600 | 2.5586 | 0.715 | | 0.0079 | 19.0 | 3800 | 2.5277 | 0.705 | | 0.005 | 20.0 | 4000 | 2.5249 | 0.6975 | ### Framework versions - Transformers 4.44.0.dev0 - Pytorch 2.4.0+cu121 - Datasets 2.20.0 - Tokenizers 0.19.1

ajrayman/Vulnerability_continuous

ajrayman

--- license: mit base_model: roberta-base tags: - generated_from_trainer model-index: - name: Vulnerability_continuous results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # Vulnerability_continuous This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.0398 - Rmse: 0.1994 - Mae: 0.1612 - Corr: 0.3525 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 32 - eval_batch_size: 32 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 2 ### Training results | Training Loss | Epoch | Step | Validation Loss | Rmse | Mae | Corr | |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:| | No log | 1.0 | 268 | 0.0402 | 0.2005 | 0.1618 | 0.3394 | | 0.0457 | 2.0 | 536 | 0.0398 | 0.1994 | 0.1612 | 0.3525 | ### Framework versions - Transformers 4.43.3 - Pytorch 2.4.0 - Datasets 2.20.0 - Tokenizers 0.19.1

QuietImpostor/Llama-31-Mini-Instruct-ft-fp16

QuietImpostor

transformers

text-generation

--- base_model: QuietImpostor/Llama-3.1-Mini-Instruct language: - en license: apache-2.0 tags: - text-generation-inference - transformers - unsloth - llama - trl - sft --- # Uploaded model - **Developed by:** QuietImpostor - **License:** apache-2.0 - **Finetuned from model :** QuietImpostor/Llama-3.1-Mini-Instruct This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library. [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)

edthrth/Security-worker-with-links-to-Mongols-offered-to-be-on-Arderns-security-team-g3-updated

edthrth

--- language: - en --- []() read the full article here : https://data.lacounty.gov/groups/9f48c48825d042f8b3ef290e70c8a114 Source : https://data.lacounty.gov/groups/772acd9e3e7343b39702eb8178436463 Flash News : https://data.lacounty.gov/groups/7af06f1aac20479182370b1a8f884648 Biden last Talk : https://huggingface.co/edthrth/43-German-shepherds-seized-by-BC-SPCA-from-property-near-Prince-George-51-updated Russian Ukrain Breaking News : https://data.lacounty.gov/groups/1f32a96d5d7a434db36f1d4d37506a69 Other Sources : https://data.iowadot.gov/groups/f00adba8005543aab1d20c68d621613f https://data.lacounty.gov/groups/33ebc015df9f42998c9b464f180863c1 https://data.lacounty.gov/groups/a6643ceecfaf4860b3e471e755da15d3 https://data.iowadot.gov/groups/7f779820ce514ffc8e2a5c015702a9a5 https://data.lacounty.gov/groups/8682f6ae93bf4ad7839cb6dbd91d04b9 https://data.lacounty.gov/groups/feaf2b038d744076b39cfed4f660a6e9 https://data.lacounty.gov/groups/728f12b842664a368ce4497a2230af22 https://data.lacounty.gov/groups/fd360d56668e47198ce687b436be3857 https://data.iowadot.gov/groups/e4279e19431d47df85e7109a01099d31 https://data.lacounty.gov/groups/8682f6ae93bf4ad7839cb6dbd91d04b9 https://data.lacounty.gov/groups/99331a60b07244858b51c86d31dd393d https://huggingface.co/edthrth/White-House-Was-Not-Aware-of-Plea-Deal-Discussions-With-September-11-Defendants-Kirby-bd-updated https://data.lacounty.gov/groups/8682f6ae93bf4ad7839cb6dbd91d04b9 https://data.lacounty.gov/groups/c5672fe31b7649e5859b3523fa4a4e95 A security guard with links to the Mongols Motorcycle Club wrote to then-Prime Minister Jacinda Ardern offering to join her security team. John Doherty also emailed the police with a proposal that he go undercover and conduct private investigations on their behalf. However, Doherty didn't hold a private investigator's licence despite advertising extensively on social media that he was about to start his own security business. "From Mobile and Static Security Patrols to Guard services, Cash and Bank Deliveries, and specialised security solutions for Weddings, Events, Functions, and more, Boulder Bank Security is your one-stop destination for premium protection," that advertisement read. Doherty even sent it directly to the police and to the Private Security Personnel Licensing Authority, which administers the kinds of licence that Doherty didn't possess. What he had was a Certificate of Approval that qualifies a person to work in positions such as a security guard or parking warden. Despite the authority reminding Doherty that he needed a separate licence to run a security business, he continued to advertise on Facebook. However, it was his links to the Mongols Motorcycle Club, a notorious criminal gang, that first called into question his suitability to hold even a Certificate of Approval and saw police apply for the authority to cancel it. At a hearing held last month, Doherty was called on to explain his links to the gang, which he applied to join in 2022. He described the members of the chapter as "clean-cut moderates" and said he wanted to join only for the camaraderie of a joint interest in American motorcycles. One of the adverts John Doherty uploaded to Facebook. Photo \/ Facebook He insisted that the Mongols were a club rather than a gang. He told the authority that his first contact with the club was to discuss siting two containers on the land surrounding its clubhouse, installing 24-hour lighting and hydroponic systems to grow berries and capsicums. "Mr Doherty's view of the Mongols and his association with them is at best naive," authority head Trish McConnell said in her recently released ruling. "It is not reasonable for anyone to think that such a horticultural system at a gang clubhouse would only be used for growing vegetables and berries." McConnell said that, if police and the Private Security Personnel Licensing Authority had known about his association with the gang, he would never have been granted his last licence. Along with Doherty's connection to the Mongols, police raised concerns about an email he sent to Ardern in 2021 offering to be part of her security detail. A police officer who spoke to him about that email said he appeared to be "delusional\....

Krabat/google-gemma-2b-1722645941

Krabat

peft

--- base_model: google/gemma-2b library_name: peft --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed] ### Framework versions - PEFT 0.12.0

edthrth/Secret-Service-to-amp-up-drone-use-after-Trump-assassination-bid-c5-updated

edthrth

--- language: - en --- []() read the full article here : https://data.lacounty.gov/groups/b72c28855c804f939a361d2ae1889d42 Source : https://data.lacounty.gov/groups/6b61baed1b2645e0a0dd784044b965aa Flash News : https://data.lacounty.gov/groups/c2f7a8458c1b4f7bbd6a55f27e229595 Biden last Talk : https://data.lacounty.gov/groups/cd3a7d916fe949f8829399b2656442e0 Russian Ukrain Breaking News : https://data.iowadot.gov/groups/ee4df13d714745b1a1c3086a528b52ac Other Sources : https://data.iowadot.gov/groups/37b2424f3a794a29b07ae1eda9795f9f https://data.lacounty.gov/groups/4b5f2e6b36a642899d2cc202900c8e70 https://data.lacounty.gov/groups/85390ac3eadd4a16a0df9ce665982c2f https://data.lacounty.gov/groups/343ed314ca81442bb932bdc016bd27b2 https://data.iowadot.gov/groups/ddf41be60549428e9c7f10117e489193 https://data.iowadot.gov/groups/06a00cdd1e164a25bf09ff3cda45a039 https://data.iowadot.gov/groups/7008c6f3be0741deb2e9d7b00ef0d934 https://groups.google.com/g/retro-comp/c/_sx74sjVs4s https://data.lacounty.gov/groups/973c51906a744b23897c135afcea7044 https://data.lacounty.gov/groups/99db01b5d24249d7a7c0ea6c4bb108fe https://data.lacounty.gov/groups/9b7604f0767a47d0984491a1e824edc0 https://data.iowadot.gov/groups/7d5eda1ed7754c74b5b4f6845b4587d2 https://data.iowadot.gov/groups/d11d07b72bc24225b661cb4f5d6c9fba https://data.lacounty.gov/groups/15a816ec1af1435e8f7735cb32493813 WASHINGTON: The US Secret Service plans to increase its use of surveillance drones following the attempted assassination of former president Donald Trump, the agency´s acting director said on Friday. "We did not have a drone on site" at the July 13 campaign rally in Butler, Pennsylvania, where a gunman opened fire on the Republican White House candidate, said Ronald Rowe, who took over after the previous director resigned. Trump was slightly wounded in the right ear, two rally attendees were seriously injured and a 50-year-old Pennsylvania firefighter was killed when the gunman, Thomas Matthew Crooks, fired eight shots from a nearby rooftop. Crooks, 20, was shot dead by a Secret Service counter-sniper on a building behind the stage where Trump had begun speaking. "We should have had better coverage on that roofline" from where Crooks opened fire, Rowe told a press conference. "We thought we might have had it covered with the human eye," he said. "But clearly we are going to change our approach now and we are going to leverage technology and put those unmanned aerial systems up."....

Tarun-1999M/code-search-net-tokenizer

Tarun-1999M

transformers

--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

abdulmanaam/distilbert-base-cased-clickbait-task1-20-epoch-post_title

abdulmanaam

--- license: apache-2.0 base_model: distilbert/distilbert-base-cased tags: - generated_from_trainer metrics: - accuracy model-index: - name: distilbert-base-cased-clickbait-task1-20-epoch-post_title results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # distilbert-base-cased-clickbait-task1-20-epoch-post_title This model is a fine-tuned version of [distilbert/distilbert-base-cased](https://huggingface.co/distilbert/distilbert-base-cased) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 2.4958 - Accuracy: 0.6475 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 20 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | No log | 1.0 | 200 | 0.8537 | 0.6225 | | No log | 2.0 | 400 | 0.8157 | 0.65 | | 0.8073 | 3.0 | 600 | 0.8731 | 0.6525 | | 0.8073 | 4.0 | 800 | 0.9890 | 0.6825 | | 0.3328 | 5.0 | 1000 | 1.2191 | 0.6325 | | 0.3328 | 6.0 | 1200 | 1.4974 | 0.675 | | 0.3328 | 7.0 | 1400 | 1.7291 | 0.6575 | | 0.0842 | 8.0 | 1600 | 1.9302 | 0.65 | | 0.0842 | 9.0 | 1800 | 2.0243 | 0.66 | | 0.0262 | 10.0 | 2000 | 2.1548 | 0.6525 | | 0.0262 | 11.0 | 2200 | 2.3360 | 0.64 | | 0.0262 | 12.0 | 2400 | 2.2967 | 0.655 | | 0.0088 | 13.0 | 2600 | 2.2970 | 0.6525 | | 0.0088 | 14.0 | 2800 | 2.3359 | 0.6425 | | 0.0058 | 15.0 | 3000 | 2.4252 | 0.6525 | | 0.0058 | 16.0 | 3200 | 2.4796 | 0.6575 | | 0.0058 | 17.0 | 3400 | 2.4698 | 0.645 | | 0.0033 | 18.0 | 3600 | 2.4963 | 0.645 | | 0.0033 | 19.0 | 3800 | 2.4821 | 0.6475 | | 0.0022 | 20.0 | 4000 | 2.4958 | 0.6475 | ### Framework versions - Transformers 4.44.0.dev0 - Pytorch 2.4.0+cu121 - Datasets 2.20.0 - Tokenizers 0.19.1

rombodawg/Mistral-Nemo-Instruct-2407-reuploaded

rombodawg

transformers

text-generation

--- language: - en library_name: transformers license: apache-2.0 tags: - mistral - unsloth - transformers --- # Finetune Mistral, Gemma, Llama 2-5x faster with 70% less memory via Unsloth! We have a free Google Colab Tesla T4 notebook for Mistral Nemo 12b here: https://colab.research.google.com/drive/17d3U-CAIwzmbDRqbZ9NnpHxCkmXB6LZ0?usp=sharing [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/Discord%20button.png" width="200"/>](https://discord.gg/u54VK8m8tk) [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/buy%20me%20a%20coffee%20button.png" width="200"/>](https://ko-fi.com/unsloth) [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth) ## ✨ Finetune for Free All notebooks are **beginner friendly**! Add your dataset, click "Run All", and you'll get a 2x faster finetuned model which can be exported to GGUF, vLLM or uploaded to Hugging Face. | Unsloth supports | Free Notebooks | Performance | Memory use | |-----------------|--------------------------------------------------------------------------------------------------------------------------|-------------|----------| | **Llama-3 8b** | [▶️ Start on Colab](https://colab.research.google.com/drive/135ced7oHytdxu3N2DNe1Z0kqjyYIkDXp?usp=sharing) | 2.4x faster | 58% less | | **Gemma 7b** | [▶️ Start on Colab](https://colab.research.google.com/drive/10NbwlsRChbma1v55m8LAPYG15uQv6HLo?usp=sharing) | 2.4x faster | 58% less | | **Mistral 7b** | [▶️ Start on Colab](https://colab.research.google.com/drive/1Dyauq4kTZoLewQ1cApceUQVNcnnNTzg_?usp=sharing) | 2.2x faster | 62% less | | **Llama-2 7b** | [▶️ Start on Colab](https://colab.research.google.com/drive/1lBzz5KeZJKXjvivbYvmGarix9Ao6Wxe5?usp=sharing) | 2.2x faster | 43% less | | **TinyLlama** | [▶️ Start on Colab](https://colab.research.google.com/drive/1AZghoNBQaMDgWJpi4RbffGM1h6raLUj9?usp=sharing) | 3.9x faster | 74% less | | **CodeLlama 34b** A100 | [▶️ Start on Colab](https://colab.research.google.com/drive/1y7A0AxE3y8gdj4AVkl2aZX47Xu3P1wJT?usp=sharing) | 1.9x faster | 27% less | | **Mistral 7b** 1xT4 | [▶️ Start on Kaggle](https://www.kaggle.com/code/danielhanchen/kaggle-mistral-7b-unsloth-notebook) | 5x faster\* | 62% less | | **DPO - Zephyr** | [▶️ Start on Colab](https://colab.research.google.com/drive/15vttTpzzVXv_tJwEk-hIcQ0S9FcEWvwP?usp=sharing) | 1.9x faster | 19% less | - This [conversational notebook](https://colab.research.google.com/drive/1Aau3lgPzeZKQ-98h69CCu1UJcvIBLmy2?usp=sharing) is useful for ShareGPT ChatML / Vicuna templates. - This [text completion notebook](https://colab.research.google.com/drive/1ef-tab5bhkvWmBOObepl1WgJvfvSzn5Q?usp=sharing) is for raw text. This [DPO notebook](https://colab.research.google.com/drive/15vttTpzzVXv_tJwEk-hIcQ0S9FcEWvwP?usp=sharing) replicates Zephyr. - \* Kaggle has 2x T4s, but we use 1. Due to overhead, 1x T4 is 5x faster.

William2357/final2

William2357

diffusers

text-to-image

--- base_model: runwayml/stable-diffusion-v1-5 library_name: diffusers license: creativeml-openrail-m tags: - text-to-image - dreambooth - diffusers-training - stable-diffusion - stable-diffusion-diffusers inference: true instance_prompt: a photo of a olis teapot --- <!-- This model card has been generated automatically according to the information the training script had access to. You should probably proofread and complete it, then remove this comment. --> # DreamBooth - William2357/final2 This is a dreambooth model derived from runwayml/stable-diffusion-v1-5. The weights were trained on a photo of a olis teapot using [DreamBooth](https://dreambooth.github.io/). You can find some example images in the following. DreamBooth for the text encoder was enabled: False. ## Intended uses & limitations #### How to use ```python # TODO: add an example code snippet for running this diffusion pipeline ``` #### Limitations and bias [TODO: provide examples of latent issues and potential remediations] ## Training details [TODO: describe the data used to train the model]

edthrth/Dozens-of-protests-planned-over-weekend-in-wake-of-Southport-attack-ef-updated

edthrth

--- language: - en --- []() read the full article here : https://data.lacounty.gov/groups/c2f7a8458c1b4f7bbd6a55f27e229595 Source : https://huggingface.co/edthrth/Nato-nukes-and-a-new-cold-war-ff-updated Flash News : https://data.lacounty.gov/groups/4b5f2e6b36a642899d2cc202900c8e70 Biden last Talk : https://data.lacounty.gov/groups/7164aa1108734b91a3b6a2514b3b1bf6 Russian Ukrain Breaking News : https://data.iowadot.gov/groups/d11d07b72bc24225b661cb4f5d6c9fba Other Sources : https://data.lacounty.gov/groups/12c17845094645d7b70e59be8f7db1bd https://data.iowadot.gov/groups/994af2af6af04d9e907c616b9b732e93 https://groups.google.com/g/sip_js/c/H4V7GQOM2F8 https://data.lacounty.gov/groups/17c95b16327042548d720aa972bc0e3e https://data.lacounty.gov/groups/b002627f93ab4c5d9eda14604cd2b3b9 https://data.lacounty.gov/groups/499ed01522f34bbea814dc8c6a20d71c https://data.lacounty.gov/groups/2f636c9996f54b00b2360ab517937bcd https://data.lacounty.gov/groups/728f12b842664a368ce4497a2230af22 https://data.lacounty.gov/groups/5bbd082d54d1401f9a23827343042900 https://data.iowadot.gov/groups/c57a4b58da7347aa96c73d9baf453195 https://data.lacounty.gov/groups/12c17845094645d7b70e59be8f7db1bd https://data.iowadot.gov/groups/07acb41d7bdb414ba78c9d34701d1145 https://data.lacounty.gov/groups/646ddebfd5da4cd587ca71ef5fa25109 https://data.iowadot.gov/groups/d11d07b72bc24225b661cb4f5d6c9fba Dozens more protests have been planned for this weekend in the wake of the Southport stabbings. Campaign group Hope Not Hate has identified more than 30 protests planned across the UK over the next two days. The knife attack at a Taylor Swift-themed dance class on Monday which left three girls dead sparked violent disorder in some cities and towns in England. Thousands of people turned out to pay their respects to the victims at a vigil in Southport on Tuesday evening, but violence later erupted outside a mosque in the town with 53 police officers and three police dogs injured. An eighth person has been arrested over the disorder in Southport on Tuesday evening. Merseyside Police said a 32-year-old man, from Wigan, was arrested on Friday on suspicion of violent disorder and remains in custody for questioning. On Wednesday evening, more than 100 protesters were arrested on Whitehall, where bottles and cans were thrown at police, and violence broke out in Hartlepool, County Durham, and in Manchester outside the Holiday Inn on Oldham Road. On Thursday, Prime Minister Sir Keir Starmer announced a new "national" response to the disorder linking police forces across the country. And on Friday evening rioters battled police in the streets of Sunderland city centre following a planned protest linked to the Southport knife attack. Hundreds of people gathered in Keel Square, many of them draped in England flags, and members of the crowd chanted in support of Tommy Robinson, while others shouted insults about Islam. Some protesters were involved in violence, setting an overturned car on fire, while others targeted a mosque. Videos posted on social media appeared to show a fire at a city centre police office, which was marked permanently closed on Google Maps and was no longer listed on a police station finder on Northumbria Police's website. Northumbria Police said in a post on X that its officers had been "subjected to serious violence\....

edthrth/Victims-in-Last-Weeks-Devils-Slide-Crash-Identified-Two-Were-US-Army-Veterans-hd-updated

edthrth

--- language: - en --- []() read the full article here : https://groups.google.com/g/retro-comp/c/BXqnB7P3ejg Source : https://groups.google.com/g/retro-comp/c/lUl-bhq-lRA Flash News : https://huggingface.co/edthrth/Dengue-Outbreak-States-Tally-Reaches-304-with-8-New-Cases-Patna-News-Times-of-India-2a-updated Biden last Talk : https://data.lacounty.gov/groups/914ecd47a1dc423b9662e1aea759db13 Russian Ukrain Breaking News : https://data.iowadot.gov/groups/c45991364bae4590863490683aae42e6 Other Sources : https://data.iowadot.gov/groups/3a8842ee5b4645d69a4079c07e54cdaf https://data.lacounty.gov/groups/c5672fe31b7649e5859b3523fa4a4e95 https://data.iowadot.gov/groups/ddf41be60549428e9c7f10117e489193 https://data.lacounty.gov/groups/64e4a44a6aed433dabd5a3e7c2df6dd5 https://data.iowadot.gov/groups/3281a2ff349d4f889acb99fcbb8a2603 https://data.lacounty.gov/groups/99331a60b07244858b51c86d31dd393d https://data.lacounty.gov/groups/4d4b58801df84a948971c9df17f95755 https://data.iowadot.gov/groups/e4279e19431d47df85e7109a01099d31 https://data.iowadot.gov/groups/bfccfe57a2f24cf9ab181f40894cc8f5 https://data.lacounty.gov/groups/499ed01522f34bbea814dc8c6a20d71c https://data.lacounty.gov/groups/9327acc6a34a4185bb315eca822bb27a https://data.lacounty.gov/groups/b216a1e12272465f88e40c30dd6b1084 https://data.lacounty.gov/groups/c2f7a8458c1b4f7bbd6a55f27e229595 https://data.lacounty.gov/groups/c5672fe31b7649e5859b3523fa4a4e95 After a car plunged 300 feet off the Highway 1 Devil's Slide area last Friday, we're now learning that the two women killed were US Army veterans, and a third man killed was a military interpreter. When news broke on Friday that a car had flown off a cliff on the Devil's Slide area on Highway 1 in San Mateo, initial reports were that two victims were found dead at the scene, and another man's body was found nearby. We now know that all three were passengers in the same vehicle, and the male was driving. This inforrmation comes in KRON4's report on the identity of all three victims; two women who were US Army veterans, and a man who had been an interpreter for the US military. The two women were Brylyn Aroma (36 years old) of Fort Riley, Kansas, and Angelica Gacho (28). The male victim was Mohammad Noory (29). Both Noory and Gaucho were reportedly South San Francisco residents. "Brylyn Andulan Aroma served as a 68W Combat Medic Specialist in the Regular Army from July 2021 to July 2024," Army spokesperson Jefferson Grimes told KRON4. "She was assigned to Fort Riley, KS, starting on October 16, 2022, and held the rank of Specialist at the end of her service. Her awards include the National Defense Service Medal, the Global War on Terrorism Service Medal, and the Army Service Ribbon. We are deeply saddened by the untimely passing of Brylyn, a Big Red One Soldier, teammate, and friend." Gacho's untimely death brought similar tributes. "Angelica Rafael Gacho served as a 92W (Water Treatment Specialist) in the Regular Army from May 2021 to October 2023. She held the rank of specialist," another Army spokesperson, Christopher Surridge, said in a statement to KRON4. "Her awards include two Army Achievement Medals, National Defense Service Medal, Korea Defense Service Medal, Army Service Ribbon, and Overseas Service Ribbon." According to a GoFundMe for Mohammad Noory, the male victim, he worked for the US military as an interpreter in Afghanistan. "Noory achieved Special Immigrant Visa (SIV) for his faithful services to the U.S. Military in Afghanistan," the GoFundMe says. "He immigrated to the U.S.A. in 2021 to provide a better future for himself and his family." That post also indicates Noory may have been driving for Uber at the time of the crash.....

Weirdkidbu8yj/Weirdkid

Weirdkidbu8yj

--- license: apache-2.0 ---

Krabat/Qwen-Qwen1.5-0.5B-1722646218

Krabat

peft

--- base_model: Qwen/Qwen1.5-0.5B library_name: peft --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed] ### Framework versions - PEFT 0.12.0

UsernameJustAnother/Nemo-12B-Marlin-v3

UsernameJustAnother

transformers

text-generation

--- base_model: unsloth/Mistral-Nemo-Instruct-2407 language: - en license: apache-2.0 tags: - text-generation-inference - transformers - unsloth - mistral - trl --- # Uploaded model - **Developed by:** UsernameJustAnother - **License:** apache-2.0 - **Finetuned from model :** unsloth/Mistral-Nemo-Instruct-2407 This mistral model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library. [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)

abdulmanaam/distilbert-base-uncased-clickbait-task1-20-epoch-post_title

abdulmanaam

--- license: apache-2.0 base_model: distilbert/distilbert-base-uncased tags: - generated_from_trainer metrics: - accuracy model-index: - name: distilbert-base-uncased-clickbait-task1-20-epoch-post_title results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # distilbert-base-uncased-clickbait-task1-20-epoch-post_title This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 2.2043 - Accuracy: 0.705 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 20 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | No log | 1.0 | 200 | 0.7890 | 0.6825 | | No log | 2.0 | 400 | 0.7432 | 0.685 | | 0.7625 | 3.0 | 600 | 0.7796 | 0.72 | | 0.7625 | 4.0 | 800 | 0.9322 | 0.6975 | | 0.3123 | 5.0 | 1000 | 1.0876 | 0.7025 | | 0.3123 | 6.0 | 1200 | 1.4319 | 0.6875 | | 0.3123 | 7.0 | 1400 | 1.6751 | 0.6725 | | 0.073 | 8.0 | 1600 | 1.7350 | 0.7075 | | 0.073 | 9.0 | 1800 | 1.8997 | 0.6875 | | 0.023 | 10.0 | 2000 | 2.0127 | 0.695 | | 0.023 | 11.0 | 2200 | 2.0654 | 0.6775 | | 0.023 | 12.0 | 2400 | 2.1128 | 0.6975 | | 0.009 | 13.0 | 2600 | 2.1777 | 0.695 | | 0.009 | 14.0 | 2800 | 2.1756 | 0.7125 | | 0.0067 | 15.0 | 3000 | 2.1566 | 0.71 | | 0.0067 | 16.0 | 3200 | 2.2452 | 0.695 | | 0.0067 | 17.0 | 3400 | 2.2008 | 0.7 | | 0.0032 | 18.0 | 3600 | 2.2214 | 0.7125 | | 0.0032 | 19.0 | 3800 | 2.2151 | 0.7125 | | 0.0041 | 20.0 | 4000 | 2.2043 | 0.705 | ### Framework versions - Transformers 4.44.0.dev0 - Pytorch 2.4.0+cu121 - Datasets 2.20.0 - Tokenizers 0.19.1

AlignmentResearch/robust_llm_b45e6244513111ef8ba9c62865e4e5e0_from_EleutherAI_pythia-14m

AlignmentResearch

Entry not found

AlignmentResearch/robust_llm_b40cdd34513111efaec5ea86182cffa1_from_EleutherAI_pythia-14m

AlignmentResearch

Entry not found

mradermacher/Meltemi-7B-v1.5-i1-GGUF

mradermacher

--- base_model: ilsp/Meltemi-7B-v1.5 language: - el - en library_name: transformers license: apache-2.0 quantized_by: mradermacher --- ## About <!-- ### quantize_version: 2 --> <!-- ### output_tensor_quantised: 1 --> <!-- ### convert_type: hf --> <!-- ### vocab_type: --> <!-- ### tags: nicoboss --> weighted/imatrix quants of https://huggingface.co/ilsp/Meltemi-7B-v1.5 <!-- provided-files --> static quants are available at https://huggingface.co/mradermacher/Meltemi-7B-v1.5-GGUF ## Usage If you are unsure how to use GGUF files, refer to one of [TheBloke's READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for more details, including on how to concatenate multi-part files. ## Provided Quants (sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants) | Link | Type | Size/GB | Notes | |:-----|:-----|--------:|:------| | [GGUF](https://huggingface.co/mradermacher/Meltemi-7B-v1.5-i1-GGUF/resolve/main/Meltemi-7B-v1.5.i1-IQ1_S.gguf) | i1-IQ1_S | 1.8 | for the desperate | | [GGUF](https://huggingface.co/mradermacher/Meltemi-7B-v1.5-i1-GGUF/resolve/main/Meltemi-7B-v1.5.i1-IQ1_M.gguf) | i1-IQ1_M | 2.0 | mostly desperate | | [GGUF](https://huggingface.co/mradermacher/Meltemi-7B-v1.5-i1-GGUF/resolve/main/Meltemi-7B-v1.5.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 2.2 | | | [GGUF](https://huggingface.co/mradermacher/Meltemi-7B-v1.5-i1-GGUF/resolve/main/Meltemi-7B-v1.5.i1-IQ2_XS.gguf) | i1-IQ2_XS | 2.4 | | | [GGUF](https://huggingface.co/mradermacher/Meltemi-7B-v1.5-i1-GGUF/resolve/main/Meltemi-7B-v1.5.i1-IQ2_S.gguf) | i1-IQ2_S | 2.5 | | | [GGUF](https://huggingface.co/mradermacher/Meltemi-7B-v1.5-i1-GGUF/resolve/main/Meltemi-7B-v1.5.i1-IQ2_M.gguf) | i1-IQ2_M | 2.7 | | | [GGUF](https://huggingface.co/mradermacher/Meltemi-7B-v1.5-i1-GGUF/resolve/main/Meltemi-7B-v1.5.i1-Q2_K.gguf) | i1-Q2_K | 3.0 | IQ3_XXS probably better | | [GGUF](https://huggingface.co/mradermacher/Meltemi-7B-v1.5-i1-GGUF/resolve/main/Meltemi-7B-v1.5.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 3.1 | lower quality | | [GGUF](https://huggingface.co/mradermacher/Meltemi-7B-v1.5-i1-GGUF/resolve/main/Meltemi-7B-v1.5.i1-IQ3_XS.gguf) | i1-IQ3_XS | 3.3 | | | [GGUF](https://huggingface.co/mradermacher/Meltemi-7B-v1.5-i1-GGUF/resolve/main/Meltemi-7B-v1.5.i1-Q3_K_S.gguf) | i1-Q3_K_S | 3.4 | IQ3_XS probably better | | [GGUF](https://huggingface.co/mradermacher/Meltemi-7B-v1.5-i1-GGUF/resolve/main/Meltemi-7B-v1.5.i1-IQ3_S.gguf) | i1-IQ3_S | 3.4 | beats Q3_K* | | [GGUF](https://huggingface.co/mradermacher/Meltemi-7B-v1.5-i1-GGUF/resolve/main/Meltemi-7B-v1.5.i1-IQ3_M.gguf) | i1-IQ3_M | 3.5 | | | [GGUF](https://huggingface.co/mradermacher/Meltemi-7B-v1.5-i1-GGUF/resolve/main/Meltemi-7B-v1.5.i1-Q3_K_M.gguf) | i1-Q3_K_M | 3.8 | IQ3_S probably better | | [GGUF](https://huggingface.co/mradermacher/Meltemi-7B-v1.5-i1-GGUF/resolve/main/Meltemi-7B-v1.5.i1-Q3_K_L.gguf) | i1-Q3_K_L | 4.1 | IQ3_M probably better | | [GGUF](https://huggingface.co/mradermacher/Meltemi-7B-v1.5-i1-GGUF/resolve/main/Meltemi-7B-v1.5.i1-IQ4_XS.gguf) | i1-IQ4_XS | 4.2 | | | [GGUF](https://huggingface.co/mradermacher/Meltemi-7B-v1.5-i1-GGUF/resolve/main/Meltemi-7B-v1.5.i1-Q4_0.gguf) | i1-Q4_0 | 4.4 | fast, low quality | | [GGUF](https://huggingface.co/mradermacher/Meltemi-7B-v1.5-i1-GGUF/resolve/main/Meltemi-7B-v1.5.i1-Q4_K_S.gguf) | i1-Q4_K_S | 4.4 | optimal size/speed/quality | | [GGUF](https://huggingface.co/mradermacher/Meltemi-7B-v1.5-i1-GGUF/resolve/main/Meltemi-7B-v1.5.i1-Q4_K_M.gguf) | i1-Q4_K_M | 4.6 | fast, recommended | | [GGUF](https://huggingface.co/mradermacher/Meltemi-7B-v1.5-i1-GGUF/resolve/main/Meltemi-7B-v1.5.i1-Q5_K_S.gguf) | i1-Q5_K_S | 5.3 | | | [GGUF](https://huggingface.co/mradermacher/Meltemi-7B-v1.5-i1-GGUF/resolve/main/Meltemi-7B-v1.5.i1-Q5_K_M.gguf) | i1-Q5_K_M | 5.4 | | | [GGUF](https://huggingface.co/mradermacher/Meltemi-7B-v1.5-i1-GGUF/resolve/main/Meltemi-7B-v1.5.i1-Q6_K.gguf) | i1-Q6_K | 6.2 | practically like static Q6_K | Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better):  And here are Artefact2's thoughts on the matter: https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9 ## FAQ / Model Request See https://huggingface.co/mradermacher/model_requests for some answers to questions you might have and/or if you want some other model quantized. ## Thanks I thank my company, [nethype GmbH](https://www.nethype.de/), for letting me use its servers and providing upgrades to my workstation to enable this work in my free time. Additional thanks to [@nicoboss](https://huggingface.co/nicoboss) for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to. <!-- end -->

MangyMango/testing1

MangyMango

Entry not found

Carbon123/PVC_Style_Model_Movable_figure_model_Pony

Carbon123

--- license: unknown ---

MangyMango/testing3

MangyMango

Entry not found

Krabat/Qwen-Qwen1.5-1.8B-1722646482

Krabat

peft

--- base_model: Qwen/Qwen1.5-1.8B library_name: peft --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed] ### Framework versions - PEFT 0.12.0

edthrth/Tunisia-women-jailed-for-buying-candidate-endorsements-c2-updated

edthrth

--- language: - en --- []() read the full article here : https://huggingface.co/edthrth/Overall-decrease-in-crime-reported-in-market-town-gf-updated Source : https://data.lacounty.gov/groups/d777d94051db48f1a84d814cfbe5be85 Flash News : https://huggingface.co/edthrth/43-German-shepherds-seized-by-BC-SPCA-from-property-near-Prince-George-1a-updated Biden last Talk : https://data.iowadot.gov/groups/899c4b461d3c4f709fe2206561efc24c Russian Ukrain Breaking News : https://huggingface.co/edthrth/The-implications-of-the-wideranging-Russia-prisoner-deal-Washington-Examiner-da-updated Other Sources : https://data.lacounty.gov/groups/4b5f2e6b36a642899d2cc202900c8e70 https://data.iowadot.gov/groups/0461d8400f6944b3b01a2d46bd4e2c1d https://data.lacounty.gov/groups/343ed314ca81442bb932bdc016bd27b2 https://data.lacounty.gov/groups/5bbd082d54d1401f9a23827343042900 https://data.lacounty.gov/groups/e85144fa94184e51afc75ffcbb8a3c6b https://data.iowadot.gov/groups/01f3c942b4b44a8585262b0b42b6febd https://data.lacounty.gov/groups/57003d2703314efdaa38e9d8764b9fc9 https://groups.google.com/g/sip_js/c/nQmRPc4fG4Q https://data.lacounty.gov/groups/beea2884544e42d2b6c007913c75cf7a https://data.iowadot.gov/groups/37b2424f3a794a29b07ae1eda9795f9f https://huggingface.co/edthrth/Congressman-LaHood-says-killing-of-Hamas-leader-in-Iran-is-justified-cf-updated https://data.lacounty.gov/groups/8b905fa804674c33b001c9bd25e57cec https://data.lacounty.gov/groups/6fb4ae28f4a7439897272faaf1eae5d5 https://data.lacounty.gov/groups/d7794f8c49ee4142b8c8162b07aa20d8 TUNIS: Tunisia has sentenced four women to jail after convicting them of buying signatures of endorsement for a would-be challenger to President Kais Saied in upcoming elections, a court spokesman said on Friday. Candidate registration for the October 6 presidential election began on Monday and closes at 5:00 pm (1600 GMT) next Tuesday. Saied critics from across the political spectrum have complained that new, tougher endorsement requirements are making it nearly impossible to get on the ballot paper. To be listed, candidates are required to provide signatures from 10,000 registered voters, with at least 500 voter signatures per constituency. "The court sentenced three women to two-year sentences, which they began serving immediately, and another, who was tried in absentia, to four years," said Alaeddine Aouadi, spokesman for the court in the northwestern town of Jendouba. At Wednesday´s hearing, the four women were also deprived of their right to vote for 10 years, Aouadi said. The women were convicted of handing over "money or gifts in kind" in exchange for voter endorsements for rapper turned businessman Karim Gharbi, better known by his stage name K2Rhym. Saied, who was democratically elected in 2019 but orchestrated a sweeping power grab in 2021, is seeking a second term. Would-be challengers include Kamel Akrout, a retired admiral, and Mondher Zenaidi, 74, a former minister who has presented his experience as an asset for debt-stricken Tunisia.....

edthrth/Russian-troops-inch-forward-in-Ukraines-east-with-waves-of-bombs-and-infantry-g4-updated

edthrth

--- language: - en --- []() read the full article here : https://groups.google.com/g/chromium-reviews-en-es/c/7FkZW7Wjg_w Source : https://data.lacounty.gov/groups/630d6f421529474da309c736f555549d Flash News : https://data.lacounty.gov/groups/6fb4ae28f4a7439897272faaf1eae5d5 Biden last Talk : https://data.lacounty.gov/groups/262caed4f6414aec9a2251ce9f58a2c4 Russian Ukrain Breaking News : https://data.lacounty.gov/groups/920ea0b30c7145bdb519839c098dc6d5 Other Sources : https://data.lacounty.gov/groups/3013a2d98f4d4b94ba2a3a5279995520 https://data.lacounty.gov/groups/b72c28855c804f939a361d2ae1889d42 https://data.lacounty.gov/groups/85390ac3eadd4a16a0df9ce665982c2f https://data.lacounty.gov/groups/772acd9e3e7343b39702eb8178436463 https://data.lacounty.gov/groups/8fe8902bcf844efda8796b929b32e4ce https://data.lacounty.gov/groups/be8bfad9c79d482aa4e33bca0513e909 https://data.lacounty.gov/groups/646ddebfd5da4cd587ca71ef5fa25109 https://data.lacounty.gov/groups/cd3a7d916fe949f8829399b2656442e0 https://huggingface.co/edthrth/Political-attacks-on-Harris-reflect-bias-ab-updated https://data.lacounty.gov/groups/cd3a7d916fe949f8829399b2656442e0 https://data.iowadot.gov/groups/994af2af6af04d9e907c616b9b732e93 https://storymaps.arcgis.com/stories/2e09af92d7634e9cbd6aa1bd75d95ddd https://data.lacounty.gov/groups/f3767f687c3748008bfb24866d36d3a2 https://data.lacounty.gov/groups/64e4a44a6aed433dabd5a3e7c2df6dd5 KYIV\/POKROVSK, Ukraine: Russian assaults are raising pressure on the strategic eastern logistics hub of Pokrovsk, Ukraine said on Friday, as waves of guided bombs and infantry lead to some of Moscow's largest territorial gains since the spring. The push is fuelling a surge in civilians fleeing, with requests for evacuation in the area increasing about tenfold over the past two weeks. Russian forces have been steadily inching forward on several fronts in the eastern Donetsk region, staging particularly fierce attacks near Pokrovsk with Kyiv's troops stretched thin 29 months since Russia's full-scale invasion. Russia's gains of around 57 square km in the space of a week are the third largest recorded since April after they made only modest gains in June, Pasi Paroinen, an analyst with the Black Bird Group, told Reuters. Russian forces are using warplanes and artillery fire to support waves of infantry assaults in the area near Pokrovsk, Ruslan Muzychuk, a spokesperson for Ukraine's National Guard said in televised remarks. "These assaults are not always supported by armoured vehicles, often it is infantry assaults," he said, flagging the bombing by Russian warplanes as a particular problem. "It's a significant threat ... because the Pokrovsk and Toretsk fronts are taking a large share of the daily aviation strikes carried out on the positions of Ukrainian defenders." Russia's Ministry of Defence said its forces had captured five settlements in the Donetsk region in the past week. Russia's use of warplanes to fire guided bombs was crucial for Moscow's battlefield tactics, said Valeriy Romanenko, a Kyiv-based aviation expert, who compared it to a "conveyor belt". "The Russians are not piercing our defence, they are pushing it back. They are advancing 100, 150, 200 metres every day using this tactic: dropping guided bombs, then a 'meat assault', (and if those are) repelled, dropping guided bombs again, a 'meat assault' again." He said the supply of US F-16 fighters to Ukraine could disrupt that dynamic if the jets were able to threaten Russian warplanes, but that such operations were unlikely for now given the risk it would present for the new pilots operating expensive jets. Paroinen said the Russian offensives around the settlements of Toretsk and Niu York as well as the one to the east of Pokrovsk around the villages of Ocheretyne and Prohres had created a "double crisis" for Ukraine towards the end of June.....

lazertorp/Qwen-Qwen1.5-0.5B-1722646523

lazertorp

peft

--- base_model: Qwen/Qwen1.5-0.5B library_name: peft --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed] ### Framework versions - PEFT 0.11.1

LLM-GAT/llama3_grad-diff_lora-256-128_beta-1p2_bs-8_lr-7e-05_checkpoint-1

LLM-GAT

transformers

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Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

LLM-GAT/llama3_grad-diff_lora-256-128_beta-1p2_bs-8_lr-7e-05_checkpoint-2

LLM-GAT

transformers

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More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

1024m/ENG-xlm-roberta-1st

1024m

Entry not found

edthrth/Air-support-to-ensure-votes-are-counted-on-time-f4-updated

edthrth

--- language: - en --- []() read the full article here : https://lookerstudio.google.com/reporting/18fea59d-0a64-4787-bc55-8ecdba2f7bfd Source : https://huggingface.co/edthrth/Illinois-Gov-JB-Pritzker-interviewed-twice-for-Kamala-Harris-VP-slot-source-says-5a-updated Flash News : https://data.iowadot.gov/groups/aa49134337364a7f9e1dc249603220f0 Biden last Talk : https://data.lacounty.gov/groups/f7e1481e87de402b9da40153f0b59904 Russian Ukrain Breaking News : https://storymaps.arcgis.com/stories/46d5deb0195740feb4bf6c438643ea2e Other Sources : https://groups.google.com/g/sip_js/c/w3JGAvHnIB8 https://data.lacounty.gov/groups/191b8d8656c142079b74f5c2fefc1794 https://data.lacounty.gov/groups/eb1fcb15716942438e22ebb1e0e0fa0c https://data.lacounty.gov/groups/f555660e657c4019909e62f5606d2fcf https://data.lacounty.gov/groups/bc1f2661f58b4d2fa0608ab91d72624b https://data.lacounty.gov/groups/8b28cb09ebf34d4486468e4484e4b8fd https://data.iowadot.gov/groups/899c4b461d3c4f709fe2206561efc24c https://data.iowadot.gov/groups/7f779820ce514ffc8e2a5c015702a9a5 https://data.lacounty.gov/groups/f8c4b606dea143f287bcb745ba278a64 https://data.iowadot.gov/groups/37b2424f3a794a29b07ae1eda9795f9f https://data.lacounty.gov/groups/a61893ea71f749928f5ff962cb539c00 https://huggingface.co/edthrth/43-German-shepherds-seized-by-BC-SPCA-from-property-near-Prince-George-ga-updated https://data.lacounty.gov/groups/18cd7b1edcee4a089f52c85c24275352 https://data.lacounty.gov/groups/dd48cfeaebf0450d9478e312a64f18dc GUA MUSANG: Two helicopters will be used for the smooth tallying of votes for the Nenggiri state by-election. Returning officer Nik Raisnan Daud said the state constituency covers a wide area including five Orang Asli posts that are located far from the vote tallying centre at Dewan Perdana, Perdana Complex of the Gua Musang District Council. "We will use the two helicopters to reach Pos Goh and Pos Simpoh because Pos Goh is 116km from Gua Musang, while Pos Simpoh is 100km away. "If we were to use a four-wheel drive vehicle, it would take six hours to get there," he told Bernama when met after inspecting preparations at the nomination centre at Dewan Perdana here yesterday. The Election Commission (EC) set today as nomination day with polling day on Aug 17, while the early voting on Aug 13 will not take place as all 14 voters involved chose to vote by post instead. The by-election is being held because the seat was declared vacant by Kelantan state assembly speaker Datuk Mohd Amar Nik Abdullah on June 19 after incumbent Mohd Azizi Abu Naim's Bersatu membership was revoked on June 13. On preparations for nomination day, Nik Raisnan said so far everything is proceeding smoothly with a simulation for the nomination process proceeding smoothly yesterday. "There will be 424 EC personnel on duty," he added. He also reminded everyone that during the nomination process, only 30 supporters for each candidate will be allowed to enter the nomination centre. "Other supporters are only allowed up to 50m from the compound," he said. Meanwhile, the media centre for the Nenggiri state by-election will start operating from today until polling day. Kelantan Information Department director Muhd Nor Aswadi Md Nor said the centre, which has Internet facilities and a place for media conferences, will operate from 9am to 7pm every day.....

edthrth/Congress-to-start-Nyay-Yatra-in-Gujarat-Rajkot-News-Times-of-India-hd-updated

edthrth

--- language: - en --- []() read the full article here : https://data.lacounty.gov/groups/b72c28855c804f939a361d2ae1889d42 Source : https://data.iowadot.gov/groups/3a8842ee5b4645d69a4079c07e54cdaf Flash News : https://data.lacounty.gov/groups/4b5f2e6b36a642899d2cc202900c8e70 Biden last Talk : https://data.lacounty.gov/groups/630d6f421529474da309c736f555549d Russian Ukrain Breaking News : https://data.lacounty.gov/groups/bfb0cf172a2842d2a1fb80164decfefc Other Sources : https://data.lacounty.gov/groups/646ddebfd5da4cd587ca71ef5fa25109 https://data.iowadot.gov/groups/cc4cbe3d97544a68b8d581a478ae1a38 https://data.lacounty.gov/groups/f8c4b606dea143f287bcb745ba278a64 https://data.iowadot.gov/groups/c45991364bae4590863490683aae42e6 https://data.iowadot.gov/groups/ee4df13d714745b1a1c3086a528b52ac https://data.lacounty.gov/groups/8b905fa804674c33b001c9bd25e57cec https://data.lacounty.gov/groups/96c82f377ff74500933a09b79bddb2f5 https://data.lacounty.gov/groups/8b28cb09ebf34d4486468e4484e4b8fd https://data.lacounty.gov/groups/973c51906a744b23897c135afcea7044 https://www.sheffield.ac.uk/js/fckeditor/editor/filemanager/browser/default/browser.html?id=howtohackaccountnnnew_3413453555&Connector=https://unitedstatednews.com https://data.lacounty.gov/groups/bfb0cf172a2842d2a1fb80164decfefc https://data.lacounty.gov/groups/499ed01522f34bbea814dc8c6a20d71c https://data.lacounty.gov/groups/728f12b842664a368ce4497a2230af22 https://data.lacounty.gov/groups/b72c28855c804f939a361d2ae1889d42 Rajkot: The Gujarat Congress will launch a "Nyay Yatra" from Aug 9, a date significant in India's freedom struggle history. Starting at Morbi and ending in Gandhinagar, the yatra aims to seek justice for the victims of various recent man-made tragedies in Gujarat. Families of the victims of the TRP Game Zone fire in Rajkot which killed 27 and the Morbi bridge collapse, which claimed 134, shook the state.The Nyay Yatra will also address the Harni boat capsize in Vadodara and the Takshashila fire in Surat will be part of the yatra. According to Congress member Lalji Desai, the yatra will begin at Morbi and reach Rajkot by the evening of August 11, where a 'Samvedna Sabha' will be organized. On the second day, the yatra will cover various areas of the city. Congress leaders have been in touch with the families of victims of all four tragedies. Around 100 participants will walk the entire route from Morbi to Gandhinagar. The yatra is to arrive in Gandhinagar by Aug 22 or 23. "The yatra won't be welcomed with beating drums, but by cotton threads. It will be a yatra in the Gandhian way," Desai said. Congress MLA Jignesh Mevani said, "We have invited all leaders to join the yatra. Rahul Gandhi, Priyanka Gandhi, Khargeji and others are expected to join it, but the dates are not certain yet."....

LLM-GAT/llama3_grad-diff_lora-256-128_beta-1p2_bs-8_lr-7e-05_checkpoint-3

LLM-GAT

transformers

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1024m/ENG-xlm-roberta-2nd

1024m

Entry not found

LLM-GAT/llama3_grad-diff_lora-256-128_beta-1p2_bs-8_lr-7e-05_checkpoint-4

LLM-GAT

transformers

--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. 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1024m/ENG-xlm-roberta-3rd

1024m

Entry not found

pavelperna/llily

pavelperna

--- license: apache-2.0 ---

LLM-GAT/llama3_grad-diff_lora-256-128_beta-1p2_bs-8_lr-7e-05_checkpoint-5

LLM-GAT

transformers

--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. 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edthrth/Russian-Prisoner-Exchange-Turkeys-Diplomatic-Coup-ExBulletin-ah-updated

edthrth

--- language: - en --- []() read the full article here : https://data.lacounty.gov/groups/7af06f1aac20479182370b1a8f884648 Source : https://data.lacounty.gov/groups/868f77ef70e64bcda92341f6b0a46d32 Flash News : https://data.lacounty.gov/groups/6d344617ead14e1daa121a7e53ea9f83 Biden last Talk : https://data.lacounty.gov/groups/18cd7b1edcee4a089f52c85c24275352 Russian Ukrain Breaking News : https://data.lacounty.gov/groups/e85144fa94184e51afc75ffcbb8a3c6b Other Sources : https://data.lacounty.gov/groups/b72c28855c804f939a361d2ae1889d42 https://data.lacounty.gov/groups/cd3a7d916fe949f8829399b2656442e0 https://data.iowadot.gov/groups/dd9c5e03371846ab95df5e86e0affe06 https://data.lacounty.gov/groups/59e66f937dff40df8c9822f168026896 https://data.lacounty.gov/groups/be8bfad9c79d482aa4e33bca0513e909 https://data.lacounty.gov/groups/262caed4f6414aec9a2251ce9f58a2c4 https://data.iowadot.gov/groups/c45991364bae4590863490683aae42e6 https://storymaps.arcgis.com/stories/94f68304792f428980bf9538ab62e9c7 https://data.lacounty.gov/groups/5ff19d3465cc40228709f73bce6432ef https://data.lacounty.gov/groups/772acd9e3e7343b39702eb8178436463 https://data.lacounty.gov/groups/bea484f911a94a2ea5a9ddb04a15ea4a https://data.lacounty.gov/groups/728f12b842664a368ce4497a2230af22 https://data.iowadot.gov/groups/dd9c5e03371846ab95df5e86e0affe06 https://data.lacounty.gov/groups/3e565394dda9416f924636520bc5b905 US President Joe Biden thanked Turkey for participating in the largest East-West exchange since the Cold War involving two dozen prisoners, including a high-ranking Russian intelligence colonel and a hitman, all gathered on the tarmac of Ankara airport. "Turkey has succeeded in a diplomatic gamble," said Sinan Ulgen, a research associate at the Carnegie Europe think tank. Turkish presidential spokesman Fahrettin Altun revealed that "Turkish intelligence has established channels of communication and mediation," showing that Turkey "is able to talk with different parties as a trustworthy and reliable partner." Months of secret negotiations leading to the deal "demonstrate the importance of Turkish diplomacy," Ulgen added, with Ankara "intervening as a facilitator or mediator in conflicts between its neighbors, particularly between Russia and the West." "This initiative gives Turkey diplomatic prestige," he said, as Ankara often strays from its traditional Western allies in the Middle East and Israel, "given its strong support for Hamas." Turkey has often presented itself as a mediator in the war in Ukraine, across the Black Sea, and in Gaza, highlighting its influence as a Muslim giant and staunch supporter of the Palestinian cause. While Turkey's vehement rhetoric against Israel has undermined its involvement in Gaza peace talks - with President Recep Tayyip Erdogan calling Prime Minister Benjamin Netanyahu a "Nazi" - Turkey could have been a key broker in negotiations between Russia and Ukraine. Ankara has maintained ties with Moscow and kyiv since the start of the war - and remains the only government to have hosted the rivals' top diplomats, Sergei Lavrov and Dmytro Kuleba, in March 2022. Erdogan has remained in direct contact with Presidents Vladimir Putin and Volodymyr Zelensky. Turkey also brokered a UN-backed deal to lift the Russian blockade on Ukrainian grain exports in 2022 and allow their safe passage across the Black Sea. Erdogan had previously mediated a prisoner exchange in September 2022 between Ukraine and Russia, which led to the release of 215 Ukrainian prisoners and the return of commanders of Ukraine's besieged Azov Brigade from Mariupol. But the Kremlin stressed Friday that any negotiations with Ukraine would be "completely different" from Thursday's exchange. By publicizing its key role, "Turkey is essentially signaling that, yes, some of its NATO allies, including the United States, may disagree with Ankara in some areas, but in other key areas, Turkey is crucial," said Soner Cagaptay of the Washington Institute for Near East Policy. "Turkey is the unsung hero of (Thursday's) prisoner swap," said Lucian Kim, Ukraine analyst for Crisis Group. "Ankara facilitated the exchange thanks to the close ties Erdogan has maintained with the Kremlin despite his NATO membership and quiet support for Ukraine," Kim said. Turkish Foreign Minister Hakan Fidan praised the role played by the MIT intelligence agency, of which he was once the director, in the exchange. The former head of Turkey's secret service promised that Turkey would "continue to be at the center of peaceful diplomacy, in line with the vision of our president." Turkey's diplomatic ambitions extend well beyond its immediate neighbors. Turkey is also trying to play a mediating role in African conflicts. Fidan will meet Ethiopian Prime Minister Abiy Ahmed in Addis Ababa on Saturday, where Turkey is pushing for peace talks between Ethiopia and Somalia, researcher Ulgen said.....

mradermacher/Med-Llama3-0.5-GGUF

mradermacher

<!-- ### quantize_version: 2 --> <!-- ### output_tensor_quantised: 1 --> <!-- ### convert_type: hf --> <!-- ### vocab_type: --> <!-- ### tags: --> static quants of https://huggingface.co/JerrySiRi/Med-Llama3-0.5

edthrth/Kamala-Harris-to-interview-final-VP-contenders-this-weekend-with-decision-imminent-ae-updated

edthrth

--- language: - en --- []() read the full article here : https://data.lacounty.gov/groups/262caed4f6414aec9a2251ce9f58a2c4 Source : https://data.lacounty.gov/groups/ee1b4221250145e7872e45bf95323709 Flash News : https://groups.google.com/g/retro-comp/c/Fp7Wb5XFS5c Biden last Talk : https://data.lacounty.gov/groups/b72c28855c804f939a361d2ae1889d42 Russian Ukrain Breaking News : https://data.lacounty.gov/groups/93a3a2660c274b478cbf762ff0750f5f Other Sources : https://data.lacounty.gov/groups/8b905fa804674c33b001c9bd25e57cec https://data.iowadot.gov/groups/01f3c942b4b44a8585262b0b42b6febd https://data.iowadot.gov/groups/45fd6b1056474423bba054f28b3083fa https://data.lacounty.gov/groups/12c17845094645d7b70e59be8f7db1bd https://data.lacounty.gov/groups/33ebc015df9f42998c9b464f180863c1 https://data.lacounty.gov/groups/e8b9788ce9b5414b976c8fe50d77c956 https://data.iowadot.gov/groups/47a596132b744265a5cb58fd9589b637 https://data.lacounty.gov/groups/f34691d7b8d344d28997367e15c9acdc https://data.lacounty.gov/groups/d3309f3de7944f2c82348f086d999553 https://data.lacounty.gov/groups/4d4b58801df84a948971c9df17f95755 https://data.iowadot.gov/groups/3a7f4b3629854b959b1753dda2ae1ed4 https://data.lacounty.gov/groups/f34691d7b8d344d28997367e15c9acdc https://groups.google.com/g/retro-comp/c/41LcczfBi48 https://huggingface.co/edthrth/Jailer-agrees-to-plead-guilty-in-case-of-inmate-who-froze-to-death-at-jail-ga-updated WASHINGTON -- Vice President Kamala Harris is set to interview her running-mate finalists over the weekend as she nears a decision amid a rapid two-week process to finalize the Democratic ticket and take on Republican nominee Donald Trump. A source familiar with the process confirmed that Harris will interview finalists among a group of six contenders who have been in the mix: Pennsylvania Gov. Josh Shapiro, U.S. Sen. Mark Kelly, D-Ariz., Minnesota Gov. Tim Walz, Transportation Secretary Pete Buttigieg, Kentucky Gov. Andy Beshear and Illinois Gov. J.B. Pritzker. Each have been vetted by the campaign. Harris, who officially became the Democratic presidential nominee by virtual roll-call on Friday, is scheduled to remain in Washington over the weekend. It was not clear how many of the final candidates Harris intends to interview. The Washington Post first reported on Harris' weekend interviews. A decision on Harris' vice presidential nominee will come no later than Tuesday, when Harris goes to Philadelphia to hold a campaign rally with her pick to kick off a multi-state battleground blitz. Launching the tour in Philadelphia raised immediate speculation about the selection being the 51-year-old Shapiro, a second-year governor from Pennsylvania and former state attorney general. Pennsylvania and its 19 electoral votes are critical to Harris' path to victory. The Harris campaign cautioned against drawing any connection. But more buzz about Shapiro ignited Friday when Philadelphia Mayor Cherelle Parker, a Democrat and Harris supporter, released a hype video that played up a Harris-Shapiro ticket. "Kamala Harris for president and Josh Shapiro for vice president," Parker says in the video, which was paid for by the mayor's campaign committee. A Harris aide would not comment on the video. Since announcing her bid for president, Harris has been riding a wave of momentum - energizing Democrats, improving upon Biden's poor polling and bringing a mountain of campaign cash. The Harris campaign announced Friday it raised $310 million in July, including $200 million in the first week of Harris' candidacy after President Joe Biden ended his reelection bid July 21. The Harris' campaign's July haul was twice the $139 million raised by Trump the same month. The Harris campaign reported having $377 million in the bank still to spend, topping the Trump campaign's $327 million cash on hand. Reach Joey Garrison on X, formerly Twitter, @joeygarrison.....

esass10/llama3-8b-exfolio-finance-test-lora

esass10

transformers

--- base_model: unsloth/llama-3-8b-bnb-4bit language: - en license: apache-2.0 tags: - text-generation-inference - transformers - unsloth - llama - trl --- # Uploaded model - **Developed by:** esass10 - **License:** apache-2.0 - **Finetuned from model :** unsloth/llama-3-8b-bnb-4bit This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library. [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)

Krabat/Qwen-Qwen1.5-7B-1722646901

Krabat

peft

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Vinacti/Voyager

Vinacti

Entry not found

LLM-GAT/llama3_grad-diff_lora-256-128_beta-1p2_bs-8_lr-7e-05_checkpoint-6

LLM-GAT

transformers

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ajrayman/Friendliness_continuous

ajrayman

--- license: mit base_model: roberta-base tags: - generated_from_trainer model-index: - name: Friendliness_continuous results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # Friendliness_continuous This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.0533 - Rmse: 0.2308 - Mae: 0.1856 - Corr: 0.2806 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 32 - eval_batch_size: 32 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 2 ### Training results | Training Loss | Epoch | Step | Validation Loss | Rmse | Mae | Corr | |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:| | No log | 1.0 | 268 | 0.0553 | 0.2351 | 0.1862 | 0.2556 | | 0.0627 | 2.0 | 536 | 0.0533 | 0.2308 | 0.1856 | 0.2806 | ### Framework versions - Transformers 4.43.3 - Pytorch 2.4.0 - Datasets 2.20.0 - Tokenizers 0.19.1

LLM-GAT/llama3_grad-diff_lora-256-128_beta-1p2_bs-8_lr-7e-05_checkpoint-7

LLM-GAT

transformers

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(2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

itorgov/model-1722647083

itorgov

Entry not found

edthrth/Ohio-women-lawmakers-face-misogyny-double-standards-when-campaigning-hh-updated

edthrth

--- language: - en --- []() read the full article here : https://data.lacounty.gov/groups/64e4a44a6aed433dabd5a3e7c2df6dd5 Source : https://data.lacounty.gov/groups/c309c0da93854b8eafc36afefead32d8 Flash News : https://huggingface.co/edthrth/Father-donates-13yearold-daughters-organs-after-kins-death-inspires-him-Bengaluru-Ne-2d-updated Biden last Talk : https://data.lacounty.gov/groups/78b1c67bcf0648f1b69a468876bbef12 Russian Ukrain Breaking News : https://data.lacounty.gov/groups/aeaad5b8b96c49dc9337907d74de0f93 Other Sources : https://data.iowadot.gov/groups/7008c6f3be0741deb2e9d7b00ef0d934 https://data.lacounty.gov/groups/9f48c48825d042f8b3ef290e70c8a114 https://data.iowadot.gov/groups/47a596132b744265a5cb58fd9589b637 https://data.lacounty.gov/groups/bf6d515bd3674b8b8ee8b85b0311ebc2 https://data.iowadot.gov/groups/c694ecb730004c149bcba1351d44a8a4 https://data.lacounty.gov/groups/17c95b16327042548d720aa972bc0e3e https://data.iowadot.gov/groups/7d5eda1ed7754c74b5b4f6845b4587d2 https://data.iowadot.gov/groups/e50aefa49baa481281c8d93c9a42a4f2 https://data.lacounty.gov/groups/af034538dd4946928e76ce709fd74fb1 https://data.lacounty.gov/groups/979fdda85abb4d69980e9a96a7040336 https://data.lacounty.gov/groups/9f48c48825d042f8b3ef290e70c8a114 https://data.lacounty.gov/groups/bc1f2661f58b4d2fa0608ab91d72624b https://data.iowadot.gov/groups/7008c6f3be0741deb2e9d7b00ef0d934 https://data.lacounty.gov/groups/59e66f937dff40df8c9822f168026896 When Kamala Harris was announced as the running mate for Joe Biden in the 2020 presidential campaign, the questions about her heritage, ethnicity and even eligibility for office came strongly from the opposition. Now that she's running for the top job following President Joe Biden's suspension of his reelection campaign, the emphasis on her skin color and her gender has come back fast and furious, just as swiftly as the enthusiasm for her campaign brings big fundraising numbers to the camp. "The United States has conflicting traditions," said Dr. Susan Burgess, distinguished professor emerita of political science at Ohio University. "One of rampant racism and misogyny, and another toward greater change and inclusion." U.S. Sen. J.D. Vance of Ohio, the vice presidential candidate alongside former president Donald Trump, added to the rhetoric in a 2021 clip that has been brought back up in light of his new role. In the clip from a Fox News interview, he mentions the fact that Harris (and others) has not birthed any children of her own (she has two stepchildren with First Gentleman Doug Emhoff), and criticizes Democrats as "a bunch of childless cat ladies who are miserable at their own lives and so they want to make the rest of the country miserable, too." https:\/\/ohiocapitaljournal.com\/2024\/08\/02\/ohio-women-lawmakers-face-misogyny-double-standards-when-campaigning\/....

LLM-GAT/llama3_grad-diff_lora-256-128_beta-1p2_bs-8_lr-7e-05_checkpoint-8

LLM-GAT

transformers

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(2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

Motocle/llm-vet-ja

Motocle

Entry not found

Krabat/google-gemma-2b-1722647115

Krabat

peft

--- base_model: google/gemma-2b library_name: peft --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed] ### Framework versions - PEFT 0.12.0

edthrth/Legionnaires-disease-outbreak-in-London-Ontario-leaves-one-dead-London-ExBulletin-5c-updated

edthrth

--- language: - en --- []() read the full article here : https://data.lacounty.gov/groups/3b4628f4ee0b4976ab77f113248d1f72 Source : https://data.iowadot.gov/groups/0096249e6fff4c509088787477f8568e Flash News : https://data.iowadot.gov/groups/ddf41be60549428e9c7f10117e489193 Biden last Talk : https://data.lacounty.gov/groups/6b61baed1b2645e0a0dd784044b965aa Russian Ukrain Breaking News : https://huggingface.co/edthrth/Secret-Service-to-amp-up-drone-use-after-Trump-assassination-bid-c5-updated Other Sources : https://data.lacounty.gov/groups/4b5f2e6b36a642899d2cc202900c8e70 https://data.lacounty.gov/groups/99db01b5d24249d7a7c0ea6c4bb108fe https://data.lacounty.gov/groups/e8b9788ce9b5414b976c8fe50d77c956 https://huggingface.co/edthrth/Obituary-for-Doris-Brown-Norman-East-Idaho-News-f5-updated https://data.iowadot.gov/groups/7b9df14337944bb6a2ed3b876f97676a https://data.lacounty.gov/groups/f8c4b606dea143f287bcb745ba278a64 https://data.lacounty.gov/groups/7164aa1108734b91a3b6a2514b3b1bf6 https://data.lacounty.gov/groups/4b5f2e6b36a642899d2cc202900c8e70 https://data.lacounty.gov/groups/a6643ceecfaf4860b3e471e755da15d3 https://data.iowadot.gov/groups/37b2424f3a794a29b07ae1eda9795f9f https://data.lacounty.gov/groups/99331a60b07244858b51c86d31dd393d https://data.iowadot.gov/groups/06a00cdd1e164a25bf09ff3cda45a039 https://data.lacounty.gov/groups/c6e2f0d1891241d497c6c03216a7e2d5 https://data.lacounty.gov/groups/ae8d0c1e810f421194d64d66db29ac36 The authorities Middlesex-London Health Authority (MLHU) confirmed one death after previously declaring Legionnaires' Disease Outbreak In the city. Health officials were first notified of the outbreak on July 24, and news of the spread emerged last week. Health officials said Friday that 22 new cases have been reported since then, with six people currently hospitalized. "All confirmed cases were hospitalized at some point during the course of their illness," the MLHU said in a statement. "There has been one death." No details regarding the identity of the deceased have been released at this time. Health authorities confirmed that most of the infected people live or work within a five-kilometer radius in the southeast of the city. Legionnaires' disease is a respiratory disease caused by a bacteria called Legionella that is usually present in hot water sources such as hot water tanks and air conditioning systems. Symptoms include high fever, chills, dry cough, shortness of breath and can lead to pneumonia. MLHU Deputy Medical Officer of Health; Dr Joan Kearon confirmed this to Global News this week. Despite the number of local cases, it does not pose a significant risk to the general public. "It's not highly contagious at all and most people who are infected don't have any symptoms," she said. Health officials say Legionnaires' disease cannot be transmitted from person to person, through public water supplies or by eating contaminated food. Most people exposed to the bacteria don't get sick or develop symptoms, but older people and those with lung disease or compromised immune systems are at higher risk of infection. "Middlesex-London Health Unit is working closely with Ontario Public Health and the Ontario Public Health Laboratory to identify the source of infection and implement action plans," the health unit continued. "An area of this size has a lot of cooling towers and other cooling equipment, so the investigation will take a long time." Officials added that it could take weeks before the source and cause of the infection is identified. "We do not recommend any changes in behavior or activities for individuals," the health authority added. The MLHU also urges all business owners and property managers to ensure that "all cooling equipment is regularly maintained and sanitized in accordance with the manufacturer's instructions."....

esass10/llama3-8b-exfolio-finance-test-q8-gguf

esass10

transformers

--- base_model: unsloth/llama-3-8b-bnb-4bit language: - en license: apache-2.0 tags: - text-generation-inference - transformers - unsloth - llama - gguf --- # Uploaded model - **Developed by:** esass10 - **License:** apache-2.0 - **Finetuned from model :** unsloth/llama-3-8b-bnb-4bit This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library. [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)

kairos54/SICU-Llama-2-7b-hf

kairos54

transformers

--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. 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Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

mradermacher/LocalAI-Llama3.1-8b-Function-Call-v0.3-i1-GGUF

mradermacher

<!-- ### quantize_version: 2 --> <!-- ### output_tensor_quantised: 1 --> <!-- ### convert_type: hf --> <!-- ### vocab_type: --> <!-- ### tags: nicoboss --> weighted/imatrix quants of https://huggingface.co/mudler/LocalAI-Llama3.1-8b-Function-Call-v0.3

Ab2143/BOT_AB

Ab2143

fasttext

robotics

--- license: mit datasets: - fka/awesome-chatgpt-prompts - proj-persona/PersonaHub language: - ar metrics: - character library_name: fasttext pipeline_tag: robotics tags: - code ---

AV3RT/Deuzenir

AV3RT

Entry not found

Iamayoutubeanimator/Bob

Iamayoutubeanimator

Entry not found

edthrth/Usha-Vance-once-appalled-and-deeply-disturbed-by-Trump-but-now-promotes-him-31-updated

edthrth

--- language: - en --- []() read the full article here : https://huggingface.co/edthrth/In-Mali-Ukraines-shadow-behind-rebels-at-war-with-Wagners-Russian-mercenaries-g5-updated Source : https://data.lacounty.gov/groups/d777d94051db48f1a84d814cfbe5be85 Flash News : https://data.lacounty.gov/groups/a61893ea71f749928f5ff962cb539c00 Biden last Talk : https://data.iowadot.gov/groups/cc4cbe3d97544a68b8d581a478ae1a38 Russian Ukrain Breaking News : https://data.iowadot.gov/groups/06a00cdd1e164a25bf09ff3cda45a039 Other Sources : https://feedbackportal.microsoft.com/feedback/idea/8dc58e6b-394f-ef11-b4ad-0022484d3ecc https://data.lacounty.gov/groups/262caed4f6414aec9a2251ce9f58a2c4 https://data.lacounty.gov/groups/c6e2f0d1891241d497c6c03216a7e2d5 https://data.lacounty.gov/groups/2e4cddeb6f494454966b4bb33b99808f https://data.iowadot.gov/groups/7836289a5f834421acb640d5242b3ea6 https://data.iowadot.gov/groups/c694ecb730004c149bcba1351d44a8a4 https://huggingface.co/edthrth/Aussies-delay-dental-treatment-as-cost-of-living-bites-1g-updated https://data.iowadot.gov/groups/c45991364bae4590863490683aae42e6 https://data.iowadot.gov/groups/45fd6b1056474423bba054f28b3083fa https://data.iowadot.gov/groups/0096249e6fff4c509088787477f8568e https://data.lacounty.gov/groups/5bbd082d54d1401f9a23827343042900 https://data.lacounty.gov/groups/33ebc015df9f42998c9b464f180863c1 https://data.lacounty.gov/groups/c6e2f0d1891241d497c6c03216a7e2d5 https://data.lacounty.gov/groups/12c17845094645d7b70e59be8f7db1bd Usha Chilukuri Vance, Sen. JD Vance's (R-Ohio) wife, hasn't been known for being publicly outspoken about politics. But according to The Washington Post, the Indian-American attorney had a lot to say privately about the Jan. 6, 2021, attack on the U.S. Capitol. And now that her husband is Donald Trump's presidential running mate, she is helping promote someone she once condemned. Post reporters Peter Jamison, Beth Reinhard, Hannah Natanson and Nicole Markus explain, "Vance told friends she was outraged by Trump's incitement of the deadly riot at the U.S. Capitol and lamented the social breakdown that fueled his political support, according to one friend, who spoke on the condition of anonymity to discuss sensitive conversations." Usha Chilukuri Vance's "view at the time," the journalists note, "contrasts with the later pronouncements of her husband and Trump's newly minted running mate, JD Vance, who has downplayed the storming of the Capitol and called participants who were jailed 'political prisoners.'" The friend told the Post, "Usha found the incursion on the Capitol and Trump's role in it to be deeply disturbing. She was generally appalled by Trump, from the moment of his first election." ALSO READ: Texas sheriffs engage conspiracy theorist who created Trump enemies 'target list' The friend added that "it was surreal to see" Usha Chilukuri Vance "sitting next to" Trump during the 2024 Republican National Convention in Milwaukee. "That sensation is widely shared among her friends, former co-workers and fellow alumni, more than two dozen of whom spoke to The Washington Post for this story," Jamison, Reinhard, Natanson and Markus report. "Some watched in disbelief on July 17 when Usha Vance, 38, addressed an overwhelmingly white crowd on the convention floor that tittered uneasily as she joked about her husband learning to cook Indian food and audibly gasped when she mentioned her vegetarian diet."....

Krabat/Qwen-Qwen1.5-0.5B-1722647393

Krabat

peft

--- base_model: Qwen/Qwen1.5-0.5B library_name: peft --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed] ### Framework versions - PEFT 0.12.0

RichardErkhov/AIFT_-_PACK-13b-v1.1-gguf

RichardErkhov

Entry not found

Legalaz/07-Mde1024197

Legalaz

Entry not found

Krabat/Qwen-Qwen1.5-1.8B-1722647660

Krabat

peft

--- base_model: Qwen/Qwen1.5-1.8B library_name: peft --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed] ### Framework versions - PEFT 0.12.0

edthrth/US-proposes-ban-on-airline-fees-for-seating-parents-next-to-kids-ea-updated

edthrth

--- language: - en --- []() read the full article here : https://data.lacounty.gov/groups/35a8a183482f4a3db0c8ac50e0a57637 Source : https://data.lacounty.gov/groups/ab2c44c67c78400aaabfaa414f2deffb Flash News : https://storymaps.arcgis.com/stories/3acc3025cd8742fd9fbe652087848ef7 Biden last Talk : https://data.lacounty.gov/groups/e48471cdff1d4ce78d9d3e1b947ef7a5 Russian Ukrain Breaking News : https://data.lacounty.gov/groups/9327acc6a34a4185bb315eca822bb27a Other Sources : https://data.lacounty.gov/groups/8682f6ae93bf4ad7839cb6dbd91d04b9 https://data.lacounty.gov/groups/4b5f2e6b36a642899d2cc202900c8e70 https://data.lacounty.gov/groups/59e66f937dff40df8c9822f168026896 https://data.iowadot.gov/groups/3281a2ff349d4f889acb99fcbb8a2603 https://data.lacounty.gov/groups/e85144fa94184e51afc75ffcbb8a3c6b https://data.lacounty.gov/groups/979fdda85abb4d69980e9a96a7040336 https://data.iowadot.gov/groups/7f779820ce514ffc8e2a5c015702a9a5 https://data.lacounty.gov/groups/d9562964497c4f31a5608a7594cd827c https://data.iowadot.gov/groups/c45991364bae4590863490683aae42e6 https://data.lacounty.gov/groups/3b4628f4ee0b4976ab77f113248d1f72 https://data.lacounty.gov/groups/35a8a183482f4a3db0c8ac50e0a57637 https://data.lacounty.gov/groups/af034538dd4946928e76ce709fd74fb1 https://data.lacounty.gov/groups/d7794f8c49ee4142b8c8162b07aa20d8 https://data.iowadot.gov/groups/47a596132b744265a5cb58fd9589b637 Parents should't have to pay a fee to sit next to their children when flying, according to the White House, which is moving to ban airlines from charging families extra to be seated together. Under a rule proposed Thursday by the Department of Transportation, airlines would be required to seat parents and kids 13 and younger together free of charge when adjacent seating is available at booking. The idea of seating adults with their younger children "is common sense and also seems like something that should be standard practice," U.S. Transportation Secretary Pete Buttigieg said at a news briefing on Wednesday. "As someone who has personally experienced flying with toddlers," Buttigieg said he knew first-hand that families traveling with little ones do not need added difficulties. "What we're doing is we are requiring that an airline not charge you extra to sit next to your kids -- or your grandkids, it applies to any company adults," Buttigieg told the CBS Mornings on Thursday. "We've gotten hundreds of complaints over this issue since I got this job and we're doing something about it." The extra cost can be the difference in whether families can afford flights for vacations or to see friends and relatives, the administration argued, noting its proposal would save a family of four up to $200 roundtrip if seat fees are $25 each. For children too young to fasten their own seatbelts or feed themselves, being seated next to a parent is crucial, yet those that don't want to pay more often end up pleading with other passengers to switch seats. If passengers opt not to swap seats, they may end up next to an unsupervised child, stressing out the youngster, parent, flight attendants and travelers, DOT said. A4A, a group representing seven major U.S. airlines, said in a statement that member carriers "make every effort to accommodate customers traveling together -- especially those traveling with children," while noting that some airlines don't charge a family seating fee. President Biden called on Congress to ban family seating and other so-called "junk" fees early last year, with Buttigieg then urging the 10 largest airlines to voluntarily ban the fees. Four complied: Alaska, American, Frontier and JetBlue. Congress gave the DOT explicit authority to propose its rule as part of the bipartisan FAA Reauthorization Act of 2024, the transportation secretary noted. "We are confident that we are well-founded in our authority, but it helps to get reassurances from Congress," Buttigieg noted in answering a question about whether the proposal might be challenged in court. A U.S. appeals court on Monday blocked the agency's new rule on upfront disclosure of airline fees pending a full view of the regulation, with the Fifth U.S. Circuit Court of Appeals saying the DOT "likely" exceeded its authority in granting an industry request for a temporary block. The DOT in April issued a mandate requiring that airlines and ticket agents disclose service fees in addition to airfares, with six carriers including American, Delta and United, along with A4A, in May suing to block the rule. In addition to banning airlines from charging fees to seat those 13 or under next to a parent or accompanying adult, the DOT's new proposal would require that airlines seat parents next to their kids within 48 hours of booking when adjacent seats are available. If adjacent seats are not available, carriers would be required to provide passengers with full refunds or the option of waiting to see if family seating frees up. If not, airlines would have to offer the option to rebook for free or stay on the flight in nonadjacent seats.....

magaman29492/blacked

magaman29492

Temporary Redirect. Redirecting to /magaman29492/Blacked-tattoo-for-ponyxl/resolve/main/README.md

edthrth/David-Cullen-Experienced-Leadership-Working-for-Us-Milwaukee-Courier-Weekly-Newspaper-5h-updated

edthrth

--- language: - en --- []() read the full article here : https://data.lacounty.gov/groups/b216a1e12272465f88e40c30dd6b1084 Source : https://data.lacounty.gov/groups/979fdda85abb4d69980e9a96a7040336 Flash News : https://data.iowadot.gov/groups/f00adba8005543aab1d20c68d621613f Biden last Talk : https://data.iowadot.gov/groups/9b3049d821174fa2827941eb6ca93618 Russian Ukrain Breaking News : https://data.lacounty.gov/groups/9b7604f0767a47d0984491a1e824edc0 Other Sources : https://huggingface.co/edthrth/Proposal-would-bar-airline-fees-for-parents-to-sit-beside-kids-1c-updated https://data.lacounty.gov/groups/979fdda85abb4d69980e9a96a7040336 https://data.lacounty.gov/groups/a61893ea71f749928f5ff962cb539c00 https://data.lacounty.gov/groups/272302a0149a489ebd9b85dee7fe6606 https://www.sheffield.ac.uk/js/fckeditor/editor/filemanager/browser/default/browser.html?id=hackear_cuentannewww_1542331112&Connector=https://unitedstatednews.com https://groups.google.com/g/codename-taurus/c/UXsw7n-4mWo https://huggingface.co/edthrth/Cognistrong-Review-Does-It-Really-Work-as-Advertised-CovingtonMaple-Valley-Reporter-24-updated https://data.lacounty.gov/groups/d7794f8c49ee4142b8c8162b07aa20d8 https://data.lacounty.gov/groups/99db01b5d24249d7a7c0ea6c4bb108fe https://data.lacounty.gov/groups/499ed01522f34bbea814dc8c6a20d71c https://data.lacounty.gov/groups/973c51906a744b23897c135afcea7044 https://data.iowadot.gov/groups/7836289a5f834421acb640d5242b3ea6 https://data.iowadot.gov/groups/7b9df14337944bb6a2ed3b876f97676a https://data.lacounty.gov/groups/ef97a3a00db74849b200c7befe7977ae EXCEPT WHERE INDICATED, THE OPINIONS EXPRESSED ON THIS PAGE ARE NOT NECESSARILY THOSE OF THE MILWAUKEE COURIER It is a privilege to serve as your Milwaukee County Treasurer. I am a lifelong resident of the City of Milwaukee. My wife and I own our home in the Enderis Park neighborhood. I am a proud graduate of John Marshall High School, the University of Wisconsin-Madison, and Marquette University Law School. The County Treasurer plays an important role in helping our community thrive. As County Treasurer, I collect delinquent property taxes from the suburban communities in Milwaukee County. The City of Milwaukee Treasurer collects delinquent property taxes from residents in the city. During my tenure as Milwaukee County Treasurer, I have collected more than $90 million in delinquent property taxes. I have used effective methods to make these collections, but have always tried to keep in mind that there can be unexpected reasons why a taxpayer has fallen behind on their property taxes. That is why I have used my experience as an attorney to negotiate more than 500 payment plans with delinquent taxpayers. These payment plans serve the dual purpose of allowing people to stay in their homes, while also collecting the taxes that are owed. Another important responsibility I have is to invest the money Milwaukee County has on hand. Our office is responsible for hundreds of millions of dollars of taxpayer money. I work with investment advisors who are experts in government investing to achieve the maximum rate of return for Milwaukee County taxpayers. In 2023 I earned $27 million in investment income for Milwaukee County. This money goes right to the county's bottom line to be used by the County Executive and County Board to fund priorities such as transit, public safety, mental health services, and county parks. I am especially proud to be the first Treasurer in history to invest significant resources in a Black-owned bank, Columbia Savings & Loan. I authorized a $250,000 investment to help Columbia Savings & Loan increase home ownership in Milwaukee's underserved neighborhoods. I am hopeful that my leadership on this issue will encourage other governmental leaders from the City of Milwaukee and the State of Wisconsin to make similar investments in our community. I have spent my career working with others to address the needs of our community. I am proud to have the support of countless leaders throughout Milwaukee County including: Congresswoman Gwen Moore City of Milwaukee Treasurer Spencer Coggs Milwaukee County Register of Deeds Israel Ramón Former Milwaukee County Treasurer Dorothy Dean State Representative Supreme Moore Omokunde State Representative Sylvia Ortiz-Velez Milwaukee County Board Chairwoman Marcelia Nicholson Milwaukee Alderwoman Sharlen Moore And many others.....

Huy227/adapter_v13

Huy227

peft

--- license: other library_name: peft tags: - llama-factory - lora - generated_from_trainer base_model: google/gemma-2-2b-it model-index: - name: dpo results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # dpo This model is a fine-tuned version of [google/gemma-2-2b-it](https://huggingface.co/google/gemma-2-2b-it) on the dpo_vi dataset. It achieves the following results on the evaluation set: - Loss: 0.6014 - Rewards/chosen: 0.4780 - Rewards/rejected: 0.2618 - Rewards/accuracies: 0.7200 - Rewards/margins: 0.2162 - Logps/rejected: -235.5573 - Logps/chosen: -250.1909 - Logits/rejected: -6.3311 - Logits/chosen: -7.0304 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-06 - train_batch_size: 1 - eval_batch_size: 1 - seed: 42 - distributed_type: multi-GPU - num_devices: 2 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - total_eval_batch_size: 2 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_ratio: 0.05 - num_epochs: 2.0 - mixed_precision_training: Native AMP ### Training results ### Framework versions - PEFT 0.12.0 - Transformers 4.43.3 - Pytorch 2.1.2 - Datasets 2.19.2 - Tokenizers 0.19.1

cswingle/test

cswingle

stable-baselines3

reinforcement-learning

--- library_name: stable-baselines3 tags: - LunarLander-v2 - deep-reinforcement-learning - reinforcement-learning - stable-baselines3 model-index: - name: PPO results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: LunarLander-v2 type: LunarLander-v2 metrics: - type: mean_reward value: 239.87 +/- 27.63 name: mean_reward verified: false --- # **PPO** Agent playing **LunarLander-v2** This is a trained model of a **PPO** agent playing **LunarLander-v2** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3). ## Usage (with Stable-baselines3) TODO: Add your code ```python from stable_baselines3 import ... from huggingface_sb3 import load_from_hub ... ```

Krabat/Qwen-Qwen1.5-7B-1722648057

Krabat

peft

--- base_model: Qwen/Qwen1.5-7B library_name: peft --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed] ### Framework versions - PEFT 0.12.0

vipin211/FineLlama-3.1-8B-LT

vipin211

transformers

text-generation

--- base_model: unsloth/Meta-Llama-3.1-8B-bnb-4bit language: - en license: apache-2.0 tags: - text-generation-inference - transformers - unsloth - llama - trl - sft --- # Uploaded model - **Developed by:** vipin211 - **License:** apache-2.0 - **Finetuned from model :** unsloth/Meta-Llama-3.1-8B-bnb-4bit This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library. [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)

ajrayman/Gregariousness_continuous

ajrayman

--- license: mit base_model: roberta-base tags: - generated_from_trainer model-index: - name: Gregariousness_continuous results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # Gregariousness_continuous This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.0569 - Rmse: 0.2386 - Mae: 0.1949 - Corr: 0.2867 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 32 - eval_batch_size: 32 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 2 ### Training results | Training Loss | Epoch | Step | Validation Loss | Rmse | Mae | Corr | |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:| | No log | 1.0 | 268 | 0.0581 | 0.2410 | 0.1977 | 0.2749 | | 0.0647 | 2.0 | 536 | 0.0569 | 0.2386 | 0.1949 | 0.2867 | ### Framework versions - Transformers 4.43.3 - Pytorch 2.4.0 - Datasets 2.20.0 - Tokenizers 0.19.1

edthrth/Hen-party-stunt-leaves-bridetobe-wearing-a-cast-for-wedding-day-3h-updated

edthrth

--- language: - en --- []() read the full article here : https://data.lacounty.gov/groups/9b7604f0767a47d0984491a1e824edc0 Source : https://data.iowadot.gov/groups/96ff76bea11747f3b0b9f0193f047b1d Flash News : https://data.lacounty.gov/groups/4d4b58801df84a948971c9df17f95755 Biden last Talk : https://data.lacounty.gov/groups/b4c93e94ca0d4fceb887ab65b80c2c08 Russian Ukrain Breaking News : https://data.lacounty.gov/groups/8b28cb09ebf34d4486468e4484e4b8fd Other Sources : https://data.lacounty.gov/groups/35a8a183482f4a3db0c8ac50e0a57637 https://data.lacounty.gov/groups/bf6d515bd3674b8b8ee8b85b0311ebc2 https://data.iowadot.gov/groups/c57a4b58da7347aa96c73d9baf453195 https://data.lacounty.gov/groups/c6e2f0d1891241d497c6c03216a7e2d5 https://data.lacounty.gov/groups/646ddebfd5da4cd587ca71ef5fa25109 https://data.lacounty.gov/groups/1f32a96d5d7a434db36f1d4d37506a69 https://data.lacounty.gov/groups/1f32a96d5d7a434db36f1d4d37506a69 https://data.lacounty.gov/groups/343ed314ca81442bb932bdc016bd27b2 https://huggingface.co/edthrth/New-hotline-numbers-available-for-mental-health-psychosocial-support-in-Bintulu-32-updated https://data.iowadot.gov/groups/6887af92d446414ab234be920970e80c https://huggingface.co/edthrth/Kamala-Harris-to-interview-final-VP-contenders-this-weekend-with-decision-imminent-ae-updated https://data.lacounty.gov/groups/bea484f911a94a2ea5a9ddb04a15ea4a https://data.iowadot.gov/groups/d204fdca49ea4344ba88574c069434df https://data.lacounty.gov/groups/17c95b16327042548d720aa972bc0e3e A bride-to-be faces walking down the aisle wearing a cast - after 'shattering' her leg during her hen do. Kurstan Buck was holidaying with her nine bridesmaids when during a party on a pontoon boat to kick start pre-wedding festivities, the bride decided to backflip into shallow water on July 9. Her bridal party watched on in horror as she backwards somersaulted into the water hitting her feet on a shallow sandbar - 'shattering' her left leg. "As the water was shallow, they took the boat to some deeper water so we could do some backflips off the boat," she said. "The lady [staff on the boat] even stood in the water to show us how deep it was but the current must have pushed the boat into shallow water without us knowing. "We got on the back of the boat to do the backflip and then as soon as we landed, I stood up and I was stunned. I was in shock. "I just hit the sand but I've heard it can be really unforgiving at how packed in it was. The sandbar was like concrete and the impact shattered my leg." The 'stunned' social media marketer said at first she was in too much shock to feel any pain after the incident in Alabama, US. After being pulled back onto the boat, she knew she had caused severe damage to her lower limb Shocking images show Kurstan's ankle swollen and with an indent on her leg where a part of her shin had caved in. After being rushed to the emergency room, doctors confirmed via x-ray that Kurstan had shattered her left tibia and broke her ankle in three places. But as her leg was too swollen to perform surgery straight away, her leg was put in a cast and the bride-to-be continued her bachelorette celebrations in a wheelchair. "We still played all the games and went for dinner and really tried to make the best out of the worst. Four days after returning home from her hen's trip on Sunday, July 14th, Kurstan went in for a five-hour operation where she had 16 screws and two plates put into her leg. Kurstan is due to marry 26-year-old Grant Hyams on October 12th this year and at first feared she would not be able to walk down the aisle on her wedding day. But after attending a check-up appointment with her surgeon he has said she should be able to walk by her big day but will be sporting a boot and cast. "I was very worried about my wedding day after my accident," she said. "I cried when my surgeon said he thinks I'll be able to walk down the aisle. This was my biggest thing as I wanted to be able to walk down the aisle. "We're going to spice my boot up and put some white stuff and bows on it. Bedazzle it up and try to make it fit in. Since her accident, Kurstan is now urging others to be careful about jumping into shallow water and admits her injuries could have been fatal if she had landed on her head or neck. "I'm very lucky that I didn't dive in and it wasn't my head and neck. As much as it hurt shattering my leg, I'm glad it was this and not my head," she said. "They tell you growing up don't dive into shallow water. They tell you this for your safety and it doesn't just apply to swimming pools."....

edthrth/Dozens-of-protests-planned-over-weekend-in-wake-of-Southport-attack-a4-updated

edthrth

--- language: - en --- []() read the full article here : https://data.iowadot.gov/groups/6887af92d446414ab234be920970e80c Source : https://data.lacounty.gov/groups/f8cf3d677f324e708859392bea6031d8 Flash News : https://data.lacounty.gov/groups/2f636c9996f54b00b2360ab517937bcd Biden last Talk : https://data.lacounty.gov/groups/beea2884544e42d2b6c007913c75cf7a Russian Ukrain Breaking News : https://data.lacounty.gov/groups/5b3c7bd15b774bb4a24b283b971723f7 Other Sources : https://data.iowadot.gov/groups/c57a4b58da7347aa96c73d9baf453195 https://data.iowadot.gov/groups/6887af92d446414ab234be920970e80c https://data.lacounty.gov/groups/f7e1481e87de402b9da40153f0b59904 https://data.iowadot.gov/groups/37b2424f3a794a29b07ae1eda9795f9f https://groups.google.com/g/luigi-user/c/AEwqm9GTQ4s https://data.lacounty.gov/groups/6d344617ead14e1daa121a7e53ea9f83 https://data.lacounty.gov/groups/262caed4f6414aec9a2251ce9f58a2c4 https://storymaps.arcgis.com/stories/5fe0021754b244a58d3a3f1f4e42cda3 https://data.lacounty.gov/groups/c6e2f0d1891241d497c6c03216a7e2d5 https://data.lacounty.gov/groups/191b8d8656c142079b74f5c2fefc1794 https://data.lacounty.gov/groups/8986eac8600e4a2d9540e2812d0c97f8 https://data.lacounty.gov/groups/f555660e657c4019909e62f5606d2fcf https://data.lacounty.gov/groups/f7e1481e87de402b9da40153f0b59904 https://data.lacounty.gov/groups/bf6d515bd3674b8b8ee8b85b0311ebc2 Dozens more protests have been planned for this weekend in the wake of the Southport stabbings. Campaign group Hope Not Hate has identified more than 30 protests planned across the UK over the next two days. The knife attack at a Taylor Swift-themed dance class on Monday which left three girls dead sparked violent disorder in some cities and towns in England. Thousands of people turned out to pay their respects to the victims at a vigil in Southport on Tuesday evening, but violence later erupted outside a mosque in the town with 53 police officers and three police dogs injured. An eighth person has been arrested over the disorder in Southport on Tuesday evening. Merseyside Police said a 32-year-old man, from Wigan, was arrested on Friday on suspicion of violent disorder and remains in custody for questioning. On Wednesday evening, more than 100 protesters were arrested on Whitehall, where bottles and cans were thrown at police, and violence broke out in Hartlepool, County Durham, and in Manchester outside the Holiday Inn on Oldham Road. On Thursday, Prime Minister Sir Keir Starmer announced a new "national" response to the disorder linking police forces across the country. And on Friday evening rioters battled police in the streets of Sunderland city centre following a planned protest linked to the Southport knife attack. Hundreds of people gathered in Keel Square, many of them draped in England flags, and members of the crowd chanted in support of Tommy Robinson, while others shouted insults about Islam. Some protesters were involved in violence, setting an overturned car on fire, while others targeted a mosque. Videos posted on social media appeared to show a fire at a city centre police office, which was marked permanently closed on Google Maps and was no longer listed on a police station finder on Northumbria Police's website. Northumbria Police said in a post on X that its officers had been "subjected to serious violence\....

MagiBoss/SeaLLMs-v3-Token-Northern

MagiBoss

peft

--- base_model: SeaLLMs/SeaLLMs-v3-7B library_name: peft license: other tags: - trl - sft - generated_from_trainer model-index: - name: SeaLLMs-v3-Token-Northern results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # SeaLLMs-v3-Token-Northern This model is a fine-tuned version of [SeaLLMs/SeaLLMs-v3-7B](https://huggingface.co/SeaLLMs/SeaLLMs-v3-7B) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.8604 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 1 - eval_batch_size: 1 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 4 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_ratio: 0.03 - num_epochs: 5 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | No log | 1.0 | 360 | 0.7886 | | 0.9075 | 2.0 | 720 | 0.7291 | | 0.5856 | 3.0 | 1080 | 0.7385 | | 0.5856 | 4.0 | 1440 | 0.7973 | | 0.3463 | 5.0 | 1800 | 0.8604 | ### Framework versions - PEFT 0.10.0 - Transformers 4.40.0 - Pytorch 2.2.2+cu121 - Datasets 2.18.0 - Tokenizers 0.19.1

DrishtiSharma/SPA-xlm-r

DrishtiSharma

Entry not found

Krabat/google-gemma-2b-1722648278

Krabat

peft

--- base_model: google/gemma-2b library_name: peft --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed] ### Framework versions - PEFT 0.12.0

edthrth/Bengal-receives-16-crore-LPG-connections-under-PMUY-scheme-Kolkata-News-Times-of-Indi-54-updated

edthrth

--- language: - en --- []() read the full article here : https://data.lacounty.gov/groups/262caed4f6414aec9a2251ce9f58a2c4 Source : https://data.lacounty.gov/groups/2f636c9996f54b00b2360ab517937bcd Flash News : https://data.lacounty.gov/groups/4d4b58801df84a948971c9df17f95755 Biden last Talk : https://data.lacounty.gov/groups/3013a2d98f4d4b94ba2a3a5279995520 Russian Ukrain Breaking News : https://data.lacounty.gov/groups/e48471cdff1d4ce78d9d3e1b947ef7a5 Other Sources : https://data.lacounty.gov/groups/a61893ea71f749928f5ff962cb539c00 https://data.lacounty.gov/groups/4b5f2e6b36a642899d2cc202900c8e70 https://data.iowadot.gov/groups/ee4df13d714745b1a1c3086a528b52ac https://lookerstudio.google.com/reporting/53a8a8f2-982e-42cc-b36d-020776d97b3b https://data.lacounty.gov/groups/3013a2d98f4d4b94ba2a3a5279995520 https://huggingface.co/edthrth/Seven-simple-diet-rules-that-every-40something-should-follow-cc-updated https://data.iowadot.gov/groups/e4279e19431d47df85e7109a01099d31 https://data.iowadot.gov/groups/d11d07b72bc24225b661cb4f5d6c9fba https://data.iowadot.gov/groups/d11d07b72bc24225b661cb4f5d6c9fba https://data.lacounty.gov/groups/a61893ea71f749928f5ff962cb539c00 https://data.iowadot.gov/groups/9b3049d821174fa2827941eb6ca93618 https://data.lacounty.gov/groups/33ebc015df9f42998c9b464f180863c1 https://data.lacounty.gov/groups/c2f7a8458c1b4f7bbd6a55f27e229595 https://data.lacounty.gov/groups/630d6f421529474da309c736f555549d Kolkata: Over 1.58 crore LPG connections have been given to subscribers in Bengal under the Pradhan Mantri Ujjwala Yojana (PMUY) schemes, said the minister of state for petroleum and natural gas Suresh Gopi in Lok Sabha on Friday. Bengal has got the most LPG connections under the scheme after UP, the minister added. Launched in 2016, PMUY provided deposit-free LPG connections for women of poor households.There are 10.33 crore PMUY beneficiaries in India. Ujjwala 2.0 was launched in Aug 2021 to cover remaining households. BJP had alleged that several households in Bengal were being refused Ujjwala connection and were told that the scheme was non-functional in the state. "Ujjwala scheme has not only empowered rural women, it has drastically reduced the use of wood and other natural resources for cooking purposes," said BJP Rajya Sabha MP Samik Bhattacharya. tnn....

edthrth/Man-dies-from-double-shooting-at-Raleigh-townhome-1-charged-with-murder-5b-updated

edthrth

--- language: - en --- []() read the full article here : https://data.iowadot.gov/groups/c45991364bae4590863490683aae42e6 Source : https://data.iowadot.gov/groups/01f3c942b4b44a8585262b0b42b6febd Flash News : https://data.lacounty.gov/groups/c2f7a8458c1b4f7bbd6a55f27e229595 Biden last Talk : https://data.iowadot.gov/groups/e4279e19431d47df85e7109a01099d31 Russian Ukrain Breaking News : https://huggingface.co/edthrth/Proposed-law-pushes-for-tougher-migrant-detention-following-Texas-girls-killing-db-updated Other Sources : https://data.iowadot.gov/groups/37b2424f3a794a29b07ae1eda9795f9f https://data.lacounty.gov/groups/78b1c67bcf0648f1b69a468876bbef12 https://data.lacounty.gov/groups/feaf2b038d744076b39cfed4f660a6e9 https://data.lacounty.gov/groups/12c17845094645d7b70e59be8f7db1bd https://data.lacounty.gov/groups/17c95b16327042548d720aa972bc0e3e https://data.lacounty.gov/groups/18cd7b1edcee4a089f52c85c24275352 https://data.lacounty.gov/groups/979fdda85abb4d69980e9a96a7040336 https://data.iowadot.gov/groups/aa49134337364a7f9e1dc249603220f0 https://data.lacounty.gov/groups/8682f6ae93bf4ad7839cb6dbd91d04b9 https://groups.google.com/g/chromium-reviews-en-es/c/QT9ilBDpxQQ https://data.lacounty.gov/groups/64e4a44a6aed433dabd5a3e7c2df6dd5 https://data.lacounty.gov/groups/630d6f421529474da309c736f555549d https://data.lacounty.gov/groups/d9562964497c4f31a5608a7594cd827c https://data.lacounty.gov/groups/7af06f1aac20479182370b1a8f884648 A man was killed and woman was seriously hurt in a shooting Friday morning at a townhome in southeast Raleigh. Before 10 a.m., officers with the Raleigh Police Department responded to 1620 Briarmont Court, located near Sunnybrook Road. There, they found a man and woman with gunshot wounds. Both were taken to a hospital with serious injuries. Around 2:30 p.m., police reported the man, Sherice Dangelo McClain, died from his injuries. McClain was 51. Julius Maurice Wilcox, 46, was arrested and charged with murder. Wilcox was also charged with assault with a dangerous weapon with intent to kill inflicting serious injury for the assault against the woman who was transported to the hospital. At 10:30 a.m., Sky 5 flew over the busy scene. There were at least 10 SUVs from the Raleigh Police Department and several EMS vehicles. Radio traffic provides more information on what happened: "Can we get EMS en route ... we got one male unconscious ineffective breathing ... got one GSW to left abdomen and another female saying she was shot ... unknown injuries." Much of the parking lot was taped off along with the rear of one townhouse. WRAL News spoke with Kendra Williams-Henrieques, the owner of a nearby Montessori school separated from the neighborhood only by a line of trees. The owner said staff heard gunshots right before the students were about to go outside for recess. She initially thought it was the sound of a vehicle backfiring. When staff heard sirens and helicopters, the took it upon themselves to lockdown the school. Williams-Henrieques said it took police over an hour to call her with information. "If there was a suspect running from the back of the location where it's taking place to the school, then we are here and essentially have no idea that something terrible could potentially be happening," she said. The Raleigh Police Department released the following statement: "Our officers' priority is to ensure public safety and to maintain the integrity of the crime scene. If we were in a position to contact a school that is within the vicinity of a crime scene, we would and those decisions are handled by responding officers who assess the urgency to make that contact. In this case, the suspect was immediately taken into custody by responding officers and contact was made with the school by phone." Police did not release the names of the victims or suspect but told WRAL News all three people involved knew each other. Anyone who believes they may have information that might assist the investigation is asked to visit Crime Stoppers at www.p3tips.com\/89 for anonymous reporting options or call 919-996-1193.....

rd211/FIXED-ASCII-LLAMA-3.1-STAGE-1-merged

rd211

transformers

text-classification

--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

mradermacher/BackToHell-GGUF

mradermacher

--- base_model: MelancholyMist/BackToHell language: - en library_name: transformers quantized_by: mradermacher --- ## About <!-- ### quantize_version: 2 --> <!-- ### output_tensor_quantised: 1 --> <!-- ### convert_type: hf --> <!-- ### vocab_type: --> <!-- ### tags: --> static quants of https://huggingface.co/MelancholyMist/BackToHell <!-- provided-files --> weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion. ## Usage If you are unsure how to use GGUF files, refer to one of [TheBloke's READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for more details, including on how to concatenate multi-part files. ## Provided Quants (sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants) | Link | Type | Size/GB | Notes | |:-----|:-----|--------:|:------| | [GGUF](https://huggingface.co/mradermacher/BackToHell-GGUF/resolve/main/BackToHell.Q2_K.gguf) | Q2_K | 0.8 | | | [GGUF](https://huggingface.co/mradermacher/BackToHell-GGUF/resolve/main/BackToHell.IQ3_XS.gguf) | IQ3_XS | 0.9 | | | [GGUF](https://huggingface.co/mradermacher/BackToHell-GGUF/resolve/main/BackToHell.IQ3_S.gguf) | IQ3_S | 0.9 | beats Q3_K* | | [GGUF](https://huggingface.co/mradermacher/BackToHell-GGUF/resolve/main/BackToHell.Q3_K_S.gguf) | Q3_K_S | 0.9 | | | [GGUF](https://huggingface.co/mradermacher/BackToHell-GGUF/resolve/main/BackToHell.IQ3_M.gguf) | IQ3_M | 0.9 | | | [GGUF](https://huggingface.co/mradermacher/BackToHell-GGUF/resolve/main/BackToHell.Q3_K_M.gguf) | Q3_K_M | 1.0 | lower quality | | [GGUF](https://huggingface.co/mradermacher/BackToHell-GGUF/resolve/main/BackToHell.Q3_K_L.gguf) | Q3_K_L | 1.0 | | | [GGUF](https://huggingface.co/mradermacher/BackToHell-GGUF/resolve/main/BackToHell.IQ4_XS.gguf) | IQ4_XS | 1.0 | | | [GGUF](https://huggingface.co/mradermacher/BackToHell-GGUF/resolve/main/BackToHell.Q4_K_S.gguf) | Q4_K_S | 1.1 | fast, recommended | | [GGUF](https://huggingface.co/mradermacher/BackToHell-GGUF/resolve/main/BackToHell.Q4_K_M.gguf) | Q4_K_M | 1.1 | fast, recommended | | [GGUF](https://huggingface.co/mradermacher/BackToHell-GGUF/resolve/main/BackToHell.Q5_K_S.gguf) | Q5_K_S | 1.3 | | | [GGUF](https://huggingface.co/mradermacher/BackToHell-GGUF/resolve/main/BackToHell.Q5_K_M.gguf) | Q5_K_M | 1.3 | | | [GGUF](https://huggingface.co/mradermacher/BackToHell-GGUF/resolve/main/BackToHell.Q6_K.gguf) | Q6_K | 1.5 | very good quality | | [GGUF](https://huggingface.co/mradermacher/BackToHell-GGUF/resolve/main/BackToHell.Q8_0.gguf) | Q8_0 | 1.9 | fast, best quality | | [GGUF](https://huggingface.co/mradermacher/BackToHell-GGUF/resolve/main/BackToHell.f16.gguf) | f16 | 3.4 | 16 bpw, overkill | Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better):  And here are Artefact2's thoughts on the matter: https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9 ## FAQ / Model Request See https://huggingface.co/mradermacher/model_requests for some answers to questions you might have and/or if you want some other model quantized. ## Thanks I thank my company, [nethype GmbH](https://www.nethype.de/), for letting me use its servers and providing upgrades to my workstation to enable this work in my free time. <!-- end -->

Krabat/Qwen-Qwen1.5-0.5B-1722648559

Krabat

peft

--- base_model: Qwen/Qwen1.5-0.5B library_name: peft --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed] ### Framework versions - PEFT 0.12.0

edthrth/Proposed-law-pushes-for-tougher-migrant-detention-following-Texas-girls-killing-ac-updated

edthrth

--- language: - en --- []() read the full article here : https://data.lacounty.gov/groups/4b5f2e6b36a642899d2cc202900c8e70 Source : https://data.lacounty.gov/groups/8b28cb09ebf34d4486468e4484e4b8fd Flash News : https://data.lacounty.gov/groups/646ddebfd5da4cd587ca71ef5fa25109 Biden last Talk : https://data.lacounty.gov/groups/f555660e657c4019909e62f5606d2fcf Russian Ukrain Breaking News : https://data.lacounty.gov/groups/9f48c48825d042f8b3ef290e70c8a114 Other Sources : https://data.iowadot.gov/groups/7836289a5f834421acb640d5242b3ea6 https://data.lacounty.gov/groups/3b4628f4ee0b4976ab77f113248d1f72 https://data.lacounty.gov/groups/15a816ec1af1435e8f7735cb32493813 https://data.lacounty.gov/groups/bfab507453c44cd0a81dbdae69305fcd https://data.iowadot.gov/groups/d11d07b72bc24225b661cb4f5d6c9fba https://data.lacounty.gov/groups/4b5f2e6b36a642899d2cc202900c8e70 https://groups.google.com/g/chromium-reviews-en-es/c/jVhkdEBfTEM https://data.lacounty.gov/groups/979fdda85abb4d69980e9a96a7040336 https://data.lacounty.gov/groups/ef97a3a00db74849b200c7befe7977ae https://data.lacounty.gov/groups/3013a2d98f4d4b94ba2a3a5279995520 https://data.lacounty.gov/groups/beea2884544e42d2b6c007913c75cf7a https://data.lacounty.gov/groups/d3309f3de7944f2c82348f086d999553 https://data.lacounty.gov/groups/17c95b16327042548d720aa972bc0e3e https://data.lacounty.gov/groups/bf6d515bd3674b8b8ee8b85b0311ebc2 HOUSTON -- Family members of a 12-year-old Houston girl who police say was killed by two Venezuelan men who entered the U.S. illegally said Friday that they are supporting legislation that would severely limit the ability of federal immigration authorities to release immigrants they detain. The proposed legislation runs counter to what migrants' rights groups advocate -- a move away from detention -- with one such advocate calling the measure an effort "to bloat the immigration enforcement system" and "to demonize immigrant communities." Venezuelan nationals Johan Jose Martinez-Rangel, 22, and Franklin Jose Peña Ramos, 26, have been charged with capital murder in the death of Jocelyn Nungaray, whose body was found in a creek June 17 after she disappeared during a walk to a convenience store. A medical examiner concluded that she was strangled. The two men entered the United States illegally earlier this year on separate occasions near El Paso. They were arrested by the U.S. Border Patrol but later released with orders to appear in court at a later date, according to the U.S. Department of Immigration and Customs Enforcement, or ICE. Their release came through ICE's Alternatives to Detention programs, which allow detained immigrants to be freed while their immigration cases are pending. ICE uses GPS monitoring, phone calls and a phone app to monitor them and ensure they make their court appearances. "The two men who ripped my daughter away from me should have never been here. They should never have been roaming our streets freely, as freely as they were," Alexis Nungaray, Jocelyn Nungaray's mother, said at a news conference. Following the girl's death, U.S. Sen. Ted Cruz and U.S. Rep. Troy Nehls, both Republicans from Texas, introduced legislation called the "Justice for Jocelyn Act." It would prevent federal authorities from releasing a detained immigrant if there are open beds available at a detention center. If detained immigrants are released, they would be subject to continuous GPS monitoring and have a nightly curfew, and any violation of the terms of their release would result in immediate deportation. "These are crimes committed by illegal immigrants who were apprehended and that the Biden-Harris administration chose to release," Cruz said. Harris County District Attorney Kim Ogg, a Democrat, said she supports the legislation because "it will make us safer and because crime is bigger than partisanship." Republicans have used recent cases of immigrants who entered the country illegally and were charged with crimes to attack what they say are President Joe Biden's failed immigration policies. In Georgia, the arrest of a Venezuelan man accused of killing nursing student Laken Hope Riley became a flashpoint in the national debate over immigration. The suspect, Jose Ibarra, appeared in court Friday as his attorneys have asked his case be moved to another county. Nayna Gupta, director of policy for the Chicago-based National Immigrant Justice Center, said the proposed legislation is "seeking to exploit ... an awful situation." Gupta said it would eliminate the limited due process that detained immigrants have to make the case that they are not a danger and should not be held in a "detention system where deaths, abuse and medical neglect are really increasing with alarming frequency." The bill's mandatory GPS monitoring would be a "huge expansion" of ICE's surveillance system, Gupta added. "This bill is just an attempt to bloat the immigration enforcement system in a politicized manner by fearmongering and using a tragic incident, again, to demonize immigrant communities," she said. A spokesperson for ICE did not immediately respond to an email seeking comment on its Alternatives to Detention programs, which have been in place since 2004. On its website, ICE says participants are thoroughly vetted and immigration officers review several factors, including criminal and supervision history and family and community ties. Migrants' rights groups have urged federal authorities to rely less on detention, saying it is inefficient and ineffective and alternatives are more humane and cost-effective. Many studies have found that immigrants are less drawn to violent crime than native-born citizens. "Does our immigration system need to be fixed? Yes. But not because of these individual crimes. It needs to be fixed because it's been broken and outdated now for decades," Gupta said.....

edthrth/Cognistrong-Review-Does-It-Really-Work-as-Advertised-CovingtonMaple-Valley-Reporter-eg-updated

edthrth

--- language: - en --- []() read the full article here : https://groups.google.com/g/chromium-reviews-en-es/c/F7yUSaYMGn8 Source : https://data.lacounty.gov/groups/93a3a2660c274b478cbf762ff0750f5f Flash News : https://data.iowadot.gov/groups/f00adba8005543aab1d20c68d621613f Biden last Talk : https://data.lacounty.gov/groups/ee1b4221250145e7872e45bf95323709 Russian Ukrain Breaking News : https://data.lacounty.gov/groups/646ddebfd5da4cd587ca71ef5fa25109 Other Sources : https://www.sheffield.ac.uk/js/fckeditor/editor/filemanager/browser/default/browser.html?id=howtohackaccountnnnew_1435214353&Connector=https://unitedstatednews.com https://data.lacounty.gov/groups/57003d2703314efdaa38e9d8764b9fc9 https://data.lacounty.gov/groups/f7e1481e87de402b9da40153f0b59904 https://groups.google.com/g/chromium-reviews-en-es/c/SIbp1toQssU https://data.lacounty.gov/groups/c5672fe31b7649e5859b3523fa4a4e95 https://data.iowadot.gov/groups/f00adba8005543aab1d20c68d621613f https://data.lacounty.gov/groups/9327acc6a34a4185bb315eca822bb27a https://data.iowadot.gov/groups/c45991364bae4590863490683aae42e6 https://data.iowadot.gov/groups/96ff76bea11747f3b0b9f0193f047b1d https://data.iowadot.gov/groups/155c6394e27a47268292a6a7b320a22d https://groups.google.com/g/sip_js/c/O6EUDqmqSBY https://data.lacounty.gov/groups/bfb0cf172a2842d2a1fb80164decfefc https://data.iowadot.gov/groups/06a00cdd1e164a25bf09ff3cda45a039 https://data.lacounty.gov/groups/cd3a7d916fe949f8829399b2656442e0 In a world filled with distractions and the ongoing pressures of everyday life, it's increasingly common for individuals to experience mental fog, forgetfulness, or a decline in cognitive performance. With these challenges, the quest for effective memory enhancement supplements has gained significant traction. Among the myriad of options available, Cognistrong stands out as a promising candidate for those seeking to improve their overall brain health. This review aims to provide a detailed analysis of Cognistrong, shedding light on its ingredients, benefits, and effectiveness while helping you determine if this supplement is the right addition to your wellness routine. Cognistrong is formulated to target cognitive decline and memory issues, which are prevalent, particularly among older demographics. Studies suggest that nearly one-third of the adult population experiences some form of memory impairment. This realization has led to an increased interest in natural supplements that claim to support brain health. Cognistrong does this through its unique blend of ingredients to enhance memory, boost cognitive function, and promote overall well-being. If you or a loved one are struggling with memory issues or wish to improve your mental abilities, understanding what Cognistrong offers could be the first step toward a clearer mind and a sharper memory. Cognistrong is a dietary supplement designed to enhance memory, improve cognitive functions, and promote overall brain health. It combines a carefully chosen blend of natural ingredients synergistically supporting brain function. The formulation targets various aspects of cognitive health, including memory retention, focus, and protection against cognitive decline. It is a comprehensive solution for anyone looking to maintain or enhance their mental capabilities. The supplement is available in easy-to-swallow veggie capsules, ensuring daily use convenience. Cognistrong is marketed towards adults of all ages, particularly those who have begun to notice a decline in their cognitive abilities due to aging or lifestyle factors. The clear labeling and strong emphasis on quality ingredients in Cognistrong set it apart from many other supplements in the market, which often lack transparency regarding their formulations. Furthermore, the creators of Cognistrong have incorporated extensive research into developing this supplement, garnering attention from health professionals and consumers alike. With positive testimonials highlighting its effectiveness, Cognistrong has quickly become a popular option for those seeking to revitalize their mental acuity. This review will delve deeper into the ingredients and benefits of Cognistrong, as well as address any concerns regarding its safety and efficacy. Get started today and see the difference Cognistrong can make! The efficacy of Cognistrong lies in its thoughtfully curated blend of ingredients, each chosen for its contributions to cognitive health. Many users have consistently reported significant improvements in memory recall, attention span, and mental clarity after using Cognistrong. These results suggest that the supplement effectively addresses the underlying factors contributing to cognitive decline, including oxidative stress and inflammation. Clinical studies surrounding the primary ingredients of Cognistrong, such as turmeric and black pepper extract, have demonstrated their capacity to enhance brain function and cognition. For instance, research has shown that curcumin, the active compound in turmeric, possesses potent neuroprotective properties, aiding in the repair of damaged brain tissues. Additionally, studies on the bioavailability-boosting properties of piper nigrum have established that taking it alongside curcumin significantly enhances its absorption, resulting in more pronounced therapeutic effects. While individual results may vary, user feedback has been largely positive, with many noting a gradual yet marked improvement in mental performance over time. This cumulative effect underlines the importance of consistent use to achieve the best results. As we further explore the specific ingredients and their benefits, you'll find compelling reasons to consider Cognistrong a viable solution for your cognitive health needs. Cognistrong is crafted with powerful, scientifically backed ingredients specifically selected for their health benefits concerning brain function. Below are the key ingredients found in Cognistrong, each contributing to its overall effectiveness. Turmeric, often referred to as a superfood, contains the potent compound curcumin. This active ingredient boasts impressive antioxidant and anti-inflammatory properties, making it a staple in traditional medicine. Curcumin has been extensively studied for its ability to support brain health and enhance cognitive function. Research indicates that curcumin plays a crucial role in reducing inflammation in the brain and protecting against age-related mental decline. By promoting the health of neurons and aiding in the regeneration of brain tissue, turmeric acts as an effective natural remedy for memory loss and cognitive impairment, making it an essential ingredient in Cognistrong. Click here to visit the official website for Cognistrong >>> Piper nigrum, commonly known as black pepper, is not just a kitchen staple but a powerful ally in enhancing the effectiveness of other nutrients. It contains piperine, which significantly increases the bioavailability of curcumin and other beneficial compounds in Cognistrong. By enhancing absorption, piper nigrum ensures that your body can utilize the full potential of curcumin and other nutrients more effectively. Additionally, piper nigrum offers various health benefits, including its potential to improve cognitive functions and protect against oxidative stress. The synergy between turmeric and piper nigrum in Cognistrong exemplifies the thoughtful formulation of this supplement. Vitamins B6 and B2 (riboflavin) are essential for optimal brain function and neurotransmitter synthesis. Vitamin B6 plays a vital role in creating neurotransmitters like serotonin, dopamine, and gamma-aminobutyric acid (GABA), crucial for mood regulation, memory, and cognition. A deficiency in vitamin B6 can lead to cognitive decline and an increased risk of neurodegenerative diseases. Meanwhile, vitamin B2 is essential for energy production within brain cells, contributing to overall cognitive efficiency and mental clarity. Including these vitamins in Cognistrong reinforces its ability to support brain health and cognitive function. Vitamin D, often associated with bone health, is critically important for brain function. Research has shown that vitamin D receptors are present in the brain, indicating its role in regulating neurological processes. Adequate vitamin D levels have been linked to improved cognitive function, mood regulation, and a reduced risk of cognitive decline as we age. In Cognition, vitamin D supports overall brain health, ensuring that cognitive processes remain sharp and effective throughout life. Get Cognistrong now while it's on sale - limited time only! Vitamin K is essential for calcium regulation within the brain and bones, crucial in maintaining cognitive function. It helps prevent oxidative damage to neural cells and supports the brain's structural integrity. Recent studies have suggested a correlation between adequate vitamin K levels and improved cognitive performance. Cognistrong includes vitamin K to enhance its protective effects against cognitive decline, ensuring that your brain remains resilient against age-related challenges. Calcium is essential in bone health, but its role in brain function is equally significant. This essential mineral is crucial for neurotransmitter release and synaptic transmission, which are fundamental processes in neural communication. Adequate calcium levels are vital for maintaining cognitive function and overall brain health. By including calcium in Cognistrong, the formulation supports optimal neurotransmitter activity, enhancing cognitive efficiency and memory retention. Selenium is a trace mineral with powerful antioxidant properties that protect against cellular damage and cognitive decline. It supports immune function and has been shown to have a beneficial impact on mood and mental performance. Research indicates that adequate selenium levels may reduce the risk of developing neurodegenerative diseases like Alzheimer's. By including selenium in Cognistrong, this supplement ensures that your brain is sufficiently protected against oxidative stress while promoting overall cognitive health. Place your order today by clicking here before stock runs out! >>> Cognistrong offers many benefits related to brain health, making it a valuable addition to anyone's daily routine. Below, we explore the key benefits associated with this powerful supplement. One of Cognistrong's standout benefits is its ability to improve memory retention and recall. The combination of ingredients such as turmeric and vitamins B6 and B2 works synergistically to enhance the brain's capacity to retrieve stored information effectively. Numerous users have reported quicker recall times, better performance in remembering names or important dates, and an overall enhancement of their day-to-day cognitive functioning. This improvement is particularly beneficial for those who find their memory diminishing with age or due to stressful lifestyles. Moreover, the neuroprotective properties of curcumin in turmeric play a crucial role in repairing brain tissues and supporting cognitive pathways. As the brain heals and regenerates, users often experience fewer forgetfulness or mental blocks, enhancing their confidence in their cognitive abilities. Cognistrong empowers individuals to remain mentally sharp and engaged in their daily lives by providing these remarkable memory-enhancing properties. Cognistrong is not just about memory; it significantly boosts overall cognitive functions, including concentration, focus, and mental clarity. The synergistic effects of potent ingredients like turmeric, piper nigrum, and essential vitamins rejuvenate brain activity, promoting enhanced mental agility. Users often report a heightened ability to concentrate on tasks without experiencing fatigue or distraction, making tackling both professional and personal responsibilities easier. The cognitive-enhancing effects of Cognistrong extend to improved problem-solving abilities and creativity. The supplement fosters an environment where the brain can function at its peak, equipping users with sharper analytical skills and innovative thinking. This boost in cognitive performance is crucial, particularly in today's fast-paced world, where the capacity to think clearly and quickly is highly valued. By incorporating Cognistrong into your daily routine, you may find yourself more productive and mentally vibrant than ever before. In an age when cognitive decline is becoming increasingly common, Cognistrong offers a formidable defense against memory-related diseases. Its ingredients' powerful antioxidant properties help to repair brain tissues, reduce inflammation, and protect brain cells from damage. Research has shown that curcumin can effectively penetrate the blood-brain barrier, exerting its protective effects directly within the brain. When used consistently, Cognistrong promotes the maintenance of healthy brain function, significantly reducing the risk of developing neurodegenerative diseases such as Alzheimer's and dementia. This protective effect is significant for individuals over 40, who may be more susceptible to cognitive decline. With Cognistrong, users can take proactive steps to safeguard their mental health, ultimately enjoying a more vibrant and fulfilling life. Order your supply of Cognistrong now and start enjoying the benefits! Chronic inflammation and oxidative stress are known contributors to cognitive decline and various neurological disorders. Cognistrong is formulated with potent antioxidants, including curcumin and selenium, which combat these harmful processes in the brain. Antioxidants help neutralize free radicals, ensuring the brain remains healthy and functional. By lowering inflammation and oxidative stress levels, Cognistrong supports cognitive health and enhances overall well-being. Users may experience improved energy levels, better mood regulation, and heightened mental clarity due to reduced inflammation. This holistic approach to brain health makes Cognistrong an ideal solution for enhancing cognitive performance and overall quality of life. Cognistrong is a carefully crafted supplement that provides essential nutrients and antioxidants to support overall brain health and function. Each ingredient has been selected for its unique properties, contributing to a comprehensive approach to cognitive enhancement. As users incorporate Cognistrong into their daily routines, they can expect improved cognitive resilience, better emotional regulation, and overall mental well-being. In addition to enhancing memory and cognitive functions, the nutritional support provided by Cognistrong promotes healthy brain aging. With regular use, individuals may find themselves experiencing a sense of mental vitality often associated with youth. By investing in your brain health through Cognistrong, you're not just addressing memory problems; you're taking proactive steps to cultivate a lifelong relationship with your mental wellness. Affordability is always a crucial consideration when purchasing supplements, and Cognistrong offers a range of pricing options to accommodate different budgets. Here's a breakdown of the available packages: Place your order right here for the best prices available! Cognistrong offers free shipping on its 3 and 6-bottle packages, making it convenient for customers looking to stock up on their supplements. Additionally, Cognistrong has a generous return policy. If customers are unsatisfied with the product, they can return it within 60 days for a full refund. This customer-friendly approach ensures you can try Cognistrong with peace of mind, knowing your investment is protected. Cognistrong is formulated with natural ingredients, which generally have fewer side effects than synthetic alternatives. Most users report minimal to no adverse reactions when taking Cognistrong as directed. However, it's essential to know that individual responses to supplements can vary. Some users may experience mild digestive discomfort, especially if they have sensitivities to supplements containing turmeric or piper nigrum. It's also advisable to consult with a healthcare professional before starting any new supplement regimen, particularly for individuals with pre-existing medical conditions or those currently taking medication. Overall, Cognistrong has been well-received by the community, with most users expressing satisfaction with its effects and minimal side effects. When taken as directed, Cognistrong is considered safe for most adults seeking to improve their memory and cognitive health. Cognistrong is produced by a dedicated team of health enthusiasts and scientific researchers committed to promoting cognitive health through natural means. The creators prioritize transparency and quality, ensuring that each ingredient meets strict standards of purity and effectiveness. The manufacturing process follows good manufacturing practices (GMP) to guarantee that Cognistrong is produced safely and consistently. This dedication to quality control ensures that customers receive a product that aligns with health standards and delivers on its promises. Furthermore, the team behind Cognistrong is passionate about educating consumers on the importance of brain health and the role of nutrition in cognitive performance. Cognistrong empowers individuals to take control of their mental health and overall well-being by promoting a well-rounded approach to brain wellness. Learn more on the official website >>> Many users of Cognistrong report positive outcomes, concluding that it indeed works. The supplement's formulation is rooted in scientific research, with each ingredient selected for its proven benefits to cognitive health. Users have experienced improvements in memory, focus, and overall mental clarity after incorporating Cognistrong into their daily routines. Long-term users have noted that Cognistrong's benefits are cumulative, indicating that consistent use is key to achieving the desired results. Most users recommend allowing the supplement to take full effect for several weeks, as the brain requires time to adapt to the nutrients provided. In essence, while individual results may vary, the overwhelming consensus among users and scientific evidence supports the effectiveness of Cognistrong in enhancing cognitive health. Cognistrong operates with transparency, high-quality ingredients, and a commitment to customer satisfaction, making it highly unlikely to be a scam. The product is backed by scientific research, and numerous testimonials from satisfied customers attest to its effectiveness in enhancing memory and cognitive function. Moreover, the 60-day money-back guarantee further emphasizes the company's confidence in the product. This assurance allows consumers to try Cognistrong without financial risk, further distancing it from scams. When considering cognitive health supplements, conducting thorough research and looking for reputable brands is essential. Cognistrong's backing by positive reviews and transparent practices positions it as a credible option in a market that can sometimes be misleading. See what others are saying about Cognistrong >>> "I was skeptical at first, but Cognistrong has changed everything for me. I've noticed such a significant improvement in my memory and concentration. I can now read and retain information without feeling overwhelmed. It feels like a weight has been lifted off my shoulders!" "After using Cognistrong for about a month, I found my mental clarity increasing daily. I no longer struggle to recall names or events, and my productivity at work has skyrocketed. I can confidently say this supplement has positively impacted my life." "I was searching for a natural way to boost my memory as I constantly forgot appointments and tasks. Cognistrong has been a game-changer. Not only do I feel sharper, but my overall mood has improved. I recommend it to anyone struggling with cognitive issues!" It's important to note that dietary supplements like Cognistrong are not subject to FDA approval in the same manner as pharmaceuticals. However, the ingredients used in Cognistrong are generally recognized as safe and are manufactured in facilities that comply with good manufacturing practices (GMP). The FDA regulates dietary supplements by ensuring that products are safe and that manufacturers' claims are truthful and not misleading. While Cognistrong is not FDA-approved, its formulation and manufacturing processes adhere to strict safety standards, ensuring that consumers receive a high-quality product. Cognistrong can conveniently be purchased through its official website. This ensures that you get an authentic product while benefiting from any promotions or discounts directly from the manufacturer. Buying from the official site also guarantees that you're eligible for the 60-day money-back guarantee should you need it. To secure your supply and take advantage of bulk purchasing options, visit the official site today. In conclusion, Cognistrong is a highly effective supplement for anyone looking to improve their memory, cognitive functions, and overall brain health. With its scientifically formulated ingredients, Cognistrong provides a natural and holistic approach to combat cognitive decline and enhance mental clarity. The positive testimonials from satisfied users and a solid refund policy make it a low-risk investment in your cognitive health. Whether you are experiencing memory issues or simply seeking to maintain your cognitive capabilities as you age, Cognistrong is worth considering. The blend of potent ingredients offers a comprehensive solution to protect your brain and boost your mental performance. By choosing Cognistrong, you're taking an essential step toward a brighter, more focused future. Cognistrong is a dietary supplement to improve memory, cognitive functions, and overall brain health. It combines natural ingredients known for their cognitive enhancing properties, targeting memory retention, focus, and protection against cognitive decline. Key ingredients include turmeric, piper nigrum, vitamins B6 and B2, vitamin D, vitamin K, calcium, and selenium, all of which contribute to cognitive health. Don't wait - click here to place your order! Users typically notice improvements in memory and focus within a few weeks of consistent use. Most users report minimal side effects. However, some may experience mild digestive discomfort. Yes, Cognistrong is formulated with natural ingredients and manufactured according to strict quality standards. It is designed for adults of all ages, but those with medical conditions should consult a healthcare professional before use. Yes, Cognistrong comes with a 60-day money-back guarantee if you are not satisfied with the product. While Cognistrong is not FDA-approved, it is manufactured in compliance with good manufacturing practices (GMP) to ensure safety and quality.....