modelId
stringlengths 5
122
| author
stringlengths 2
42
| last_modified
unknown | downloads
int64 0
434M
| likes
int64 0
6.52k
| library_name
stringclasses 346
values | tags
sequencelengths 1
4.05k
| pipeline_tag
stringclasses 51
values | createdAt
unknown | card
stringlengths 1
913k
|
---|---|---|---|---|---|---|---|---|---|
Struggler41/AlixVoiceAi | Struggler41 | "2024-02-03T00:23:16Z" | 0 | 0 | null | [
"license:unknown",
"region:us"
] | null | "2024-02-02T23:55:27Z" | ---
license: unknown
---
|
jljl1337/svc-toolkit | jljl1337 | "2024-04-04T16:03:46Z" | 0 | 1 | null | [
"region:us"
] | null | "2024-02-02T23:56:50Z" | Entry not found |
birgermoell/MOE-SWE-DAN-NO-CODE | birgermoell | "2024-02-02T23:59:23Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-02-02T23:59:23Z" | Entry not found |
Simomh/MQuant | Simomh | "2024-02-03T00:01:22Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-02-03T00:01:22Z" | Entry not found |
johnnybop/Vic | johnnybop | "2024-02-03T00:09:01Z" | 0 | 0 | null | [
"license:apache-2.0",
"region:us"
] | null | "2024-02-03T00:06:42Z" | ---
license: apache-2.0
---
|
Milanesa16/JeonHyeYoung | Milanesa16 | "2024-02-03T00:23:40Z" | 0 | 0 | null | [
"license:openrail",
"region:us"
] | null | "2024-02-03T00:10:22Z" | ---
license: openrail
---
|
princessofdarkness/MShadows | princessofdarkness | "2024-02-03T00:21:47Z" | 0 | 1 | null | [
"region:us"
] | null | "2024-02-03T00:21:06Z" | Entry not found |
raskylark/makima_chainsawman | raskylark | "2024-02-03T00:38:27Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-02-03T00:26:57Z" | Entry not found |
victorcata/Model_demo | victorcata | "2024-02-03T00:28:01Z" | 0 | 0 | null | [
"license:mit",
"region:us"
] | null | "2024-02-03T00:28:01Z" | ---
license: mit
---
|
tom192180/distilbert-base-uncased_odm_zphr_0st_ut72ut1_plainValPrefix0stlarge_simsp | tom192180 | "2024-02-03T00:37:33Z" | 0 | 0 | transformers | [
"transformers",
"safetensors",
"distilbert",
"text-classification",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text-classification | "2024-02-03T00:32:33Z" | Entry not found |
4naluvs/TAEHYUNG_Strong | 4naluvs | "2024-02-03T00:39:50Z" | 0 | 0 | null | [
"license:openrail",
"region:us"
] | null | "2024-02-03T00:38:37Z" | ---
license: openrail
---
|
raskylark/nami_onepiece | raskylark | "2024-02-03T00:58:38Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-02-03T00:39:59Z" | Entry not found |
r3m3c3/english-to-kanji-c7000_model_3_v_0 | r3m3c3 | "2024-02-03T00:46:53Z" | 0 | 0 | diffusers | [
"diffusers",
"safetensors",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | "2024-02-03T00:45:42Z" | ---
library_name: diffusers
---
# 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 🧨 diffusers 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]
|
r3m3c3/english-to-kanji-c8000_model_3_v_0 | r3m3c3 | "2024-02-03T00:50:56Z" | 0 | 0 | diffusers | [
"diffusers",
"safetensors",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | "2024-02-03T00:49:43Z" | ---
library_name: diffusers
---
# 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 🧨 diffusers 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]
|
r3m3c3/english-to-kanji-c12000_model_3_v_0 | r3m3c3 | "2024-02-03T00:52:52Z" | 0 | 0 | diffusers | [
"diffusers",
"safetensors",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | "2024-02-03T00:51:41Z" | ---
library_name: diffusers
---
# 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 🧨 diffusers 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]
|
mlc-ai/stablelm-2-zephyr-1_6b-q0f16_1-MLC | mlc-ai | "2024-07-11T15:32:35Z" | 0 | 0 | mlc-llm | [
"mlc-llm",
"web-llm",
"base_model:stabilityai/stablelm-2-zephyr-1_6b",
"base_model:quantized:stabilityai/stablelm-2-zephyr-1_6b",
"region:us"
] | null | "2024-02-03T00:52:18Z" | ---
library_name: mlc-llm
base_model: stabilityai/stablelm-2-zephyr-1_6b
tags:
- mlc-llm
- web-llm
---
# stablelm-2-zephyr-1_6b-q0f16_1-MLC
This is the [stablelm-2-zephyr-1_6b](https://huggingface.co/stabilityai/stablelm-2-zephyr-1_6b) model in MLC format `q0f16_1`.
The model can be used for projects [MLC-LLM](https://github.com/mlc-ai/mlc-llm) and [WebLLM](https://github.com/mlc-ai/web-llm).
## Example Usage
Here are some examples of using this model in MLC LLM.
Before running the examples, please install MLC LLM by following the [installation documentation](https://llm.mlc.ai/docs/install/mlc_llm.html#install-mlc-packages).
### Chat
In command line, run
```bash
mlc_llm chat HF://mlc-ai/stablelm-2-zephyr-1_6b-q0f16_1-MLC
```
### REST Server
In command line, run
```bash
mlc_llm serve HF://mlc-ai/stablelm-2-zephyr-1_6b-q0f16_1-MLC
```
### Python API
```python
from mlc_llm import MLCEngine
# Create engine
model = "HF://mlc-ai/stablelm-2-zephyr-1_6b-q0f16_1-MLC"
engine = MLCEngine(model)
# Run chat completion in OpenAI API.
for response in engine.chat.completions.create(
messages=[{"role": "user", "content": "What is the meaning of life?"}],
model=model,
stream=True,
):
for choice in response.choices:
print(choice.delta.content, end="", flush=True)
print("\n")
engine.terminate()
```
## Documentation
For more information on MLC LLM project, please visit our [documentation](https://llm.mlc.ai/docs/) and [GitHub repo](http://github.com/mlc-ai/mlc-llm).
|
r3m3c3/english-to-kanji-c14500_model_3_v_0 | r3m3c3 | "2024-02-03T00:54:49Z" | 0 | 0 | diffusers | [
"diffusers",
"safetensors",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | "2024-02-03T00:53:26Z" | ---
library_name: diffusers
---
# 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 🧨 diffusers 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]
|
r3m3c3/english-to-kanji-c18000_model_3_v_0 | r3m3c3 | "2024-02-03T00:58:26Z" | 0 | 0 | diffusers | [
"diffusers",
"safetensors",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | "2024-02-03T00:57:19Z" | ---
library_name: diffusers
---
# 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 🧨 diffusers 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]
|
mlc-ai/stablelm-zephyr-3b-q0f16-MLC | mlc-ai | "2024-07-11T15:32:36Z" | 0 | 0 | mlc-llm | [
"mlc-llm",
"web-llm",
"base_model:stabilityai/stablelm-zephyr-3b",
"base_model:quantized:stabilityai/stablelm-zephyr-3b",
"region:us"
] | null | "2024-02-03T00:59:01Z" | ---
library_name: mlc-llm
base_model: stabilityai/stablelm-zephyr-3b
tags:
- mlc-llm
- web-llm
---
# stablelm-zephyr-3b-q0f16-MLC
This is the [stablelm-zephyr-3b](https://huggingface.co/stabilityai/stablelm-zephyr-3b) model in MLC format `q0f16`.
The model can be used for projects [MLC-LLM](https://github.com/mlc-ai/mlc-llm) and [WebLLM](https://github.com/mlc-ai/web-llm).
## Example Usage
Here are some examples of using this model in MLC LLM.
Before running the examples, please install MLC LLM by following the [installation documentation](https://llm.mlc.ai/docs/install/mlc_llm.html#install-mlc-packages).
### Chat
In command line, run
```bash
mlc_llm chat HF://mlc-ai/stablelm-zephyr-3b-q0f16-MLC
```
### REST Server
In command line, run
```bash
mlc_llm serve HF://mlc-ai/stablelm-zephyr-3b-q0f16-MLC
```
### Python API
```python
from mlc_llm import MLCEngine
# Create engine
model = "HF://mlc-ai/stablelm-zephyr-3b-q0f16-MLC"
engine = MLCEngine(model)
# Run chat completion in OpenAI API.
for response in engine.chat.completions.create(
messages=[{"role": "user", "content": "What is the meaning of life?"}],
model=model,
stream=True,
):
for choice in response.choices:
print(choice.delta.content, end="", flush=True)
print("\n")
engine.terminate()
```
## Documentation
For more information on MLC LLM project, please visit our [documentation](https://llm.mlc.ai/docs/) and [GitHub repo](http://github.com/mlc-ai/mlc-llm).
|
r3m3c3/english-to-kanji-c20000_model_3_v_0 | r3m3c3 | "2024-02-03T01:01:22Z" | 0 | 0 | diffusers | [
"diffusers",
"safetensors",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | "2024-02-03T01:00:15Z" | ---
library_name: diffusers
---
# 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 🧨 diffusers 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]
|
karawalla/aqmodel_20240203 | karawalla | "2024-02-03T01:02:25Z" | 0 | 0 | transformers | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | "2024-02-03T01:02:19Z" | ---
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]
|
r3m3c3/english-to-kanji-c23000_model_3_v_0 | r3m3c3 | "2024-02-03T01:04:24Z" | 0 | 0 | diffusers | [
"diffusers",
"safetensors",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | "2024-02-03T01:03:05Z" | ---
library_name: diffusers
---
# 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 🧨 diffusers 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]
|
Tsuinzues/matheusmaxvoz | Tsuinzues | "2024-02-03T01:07:26Z" | 0 | 0 | null | [
"license:openrail",
"region:us"
] | null | "2024-02-03T01:07:12Z" | ---
license: openrail
---
|
r3m3c3/english-to-kanji-c29000_model_3_v_0 | r3m3c3 | "2024-02-03T01:12:03Z" | 0 | 0 | diffusers | [
"diffusers",
"safetensors",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | "2024-02-03T01:10:52Z" | ---
library_name: diffusers
---
# 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 🧨 diffusers 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]
|
sourenp/cars-trucks-other | sourenp | "2024-02-03T01:13:27Z" | 0 | 0 | null | [
"license:apache-2.0",
"region:us"
] | null | "2024-02-03T01:12:19Z" | ---
license: apache-2.0
---
|
Freddie-Dassin/Nepptenio | Freddie-Dassin | "2024-02-03T01:16:17Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-02-03T01:14:08Z" | Entry not found |
r3m3c3/english-to-kanji-c36500_model_3_v_0 | r3m3c3 | "2024-02-03T01:18:55Z" | 0 | 0 | diffusers | [
"diffusers",
"safetensors",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | "2024-02-03T01:17:36Z" | ---
library_name: diffusers
---
# 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 🧨 diffusers 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]
|
salapierrot16/malosinger | salapierrot16 | "2024-02-03T01:24:11Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-02-03T01:24:06Z" | Entry not found |
CyberHarem/dagda_arknights | CyberHarem | "2024-03-26T05:10:00Z" | 0 | 0 | null | [
"art",
"not-for-all-audiences",
"text-to-image",
"dataset:CyberHarem/dagda_arknights",
"license:mit",
"region:us"
] | text-to-image | "2024-02-03T01:25:02Z" | ---
license: mit
datasets:
- CyberHarem/dagda_arknights
pipeline_tag: text-to-image
tags:
- art
- not-for-all-audiences
---
# LoRA model of dagda/ダグザ/达格达 (Arknights)
## What Is This?
This is the LoRA model of waifu dagda/ダグザ/达格达 (Arknights).
## How Is It Trained?
* This model is trained with [kohya-ss/sd-scripts](https://github.com/kohya-ss/sd-scripts), and the test images are generated with [a1111's webui](AUTOMATIC1111/stable-diffusion-webui) and [API sdk](https://github.com/mix1009/sdwebuiapi).
* The [auto-training framework](https://github.com/deepghs/cyberharem) is maintained by [DeepGHS Team](https://huggingface.co/deepghs).
The architecture of base model is is `SD1.5`.
* Dataset used for training is the `stage3-p480-1200` in [CyberHarem/dagda_arknights](https://huggingface.co/datasets/CyberHarem/dagda_arknights), which contains 98 images.
* **Trigger word is `dagda_arknights`.**
* Pruned core tags for this waifu are `black hair, animal ears, cat ears, long hair, yellow eyes, hair between eyes, tail, very long hair, cat tail, cat girl, extra ears, ear piercing, earrings`. You can add them to the prompt when some features of waifu (e.g. hair color) are not stable.
* For more details in training, you can take a look at [training configuration file](https://huggingface.co/CyberHarem/dagda_arknights/resolve/main/train.toml).
* For more details in LoRA, you can download it, and read the metadata with a1111's webui.
## How to Use It?
After downloading the safetensors files for the specified step, you need to use them like common LoRA.
* Recommended LoRA weight is 0.5-0.85.
* Recommended trigger word weight is 0.7-1.1.
For example, if you want to use the model from step 1287, you need to download [`1287/dagda_arknights.safetensors`](https://huggingface.co/CyberHarem/dagda_arknights/resolve/main/1287/dagda_arknights.safetensors) as LoRA. By using this model, you can generate images for the desired characters.
## Which Step Should I Use?
We selected 5 good steps for you to choose. The best one is step 1287.
1026 images (1.03 GiB) were generated for auto-testing.
![Metrics Plot](metrics_plot.png)
The base model used for generating preview images is [meinamix_v11](https://huggingface.co/meinamix_v11).
Here are the preview of the recommended steps:
| Step | Epoch | CCIP | AI Corrupt | Bikini Plus | Score | Download | pattern_0_0 | pattern_0_1 | pattern_1 | portrait_0 | portrait_1 | portrait_2 | full_body_0 | full_body_1 | profile_0 | profile_1 | free_0 | free_1 | shorts | maid_0 | maid_1 | miko | yukata | suit | china | bikini_0 | bikini_1 | bikini_2 | sit | squat | kneel | jump | crossed_arms | angry | smile | cry | grin | n_lie_0 | n_lie_1 | n_stand_0 | n_stand_1 | n_stand_2 | n_sex_0 | n_sex_1 |
|-------:|--------:|:----------|:-------------|:--------------|:----------|:----------------------------------------------------------------------------------------------------|:----------------------------------------------|:----------------------------------------------|:------------------------------------------|:--------------------------------------------|:--------------------------------------------|:--------------------------------------------|:----------------------------------------------|:----------------------------------------------|:------------------------------------------|:------------------------------------------|:------------------------------------|:------------------------------------|:------------------------------------|:------------------------------------|:------------------------------------|:--------------------------------|:------------------------------------|:--------------------------------|:----------------------------------|:----------------------------------------|:----------------------------------------|:----------------------------------------|:------------------------------|:----------------------------------|:----------------------------------|:--------------------------------|:------------------------------------------------|:----------------------------------|:----------------------------------|:------------------------------|:--------------------------------|:--------------------------------------|:--------------------------------------|:------------------------------------------|:------------------------------------------|:------------------------------------------|:--------------------------------------|:--------------------------------------|
| 1287 | 39 | **0.964** | 0.985 | 0.847 | **0.911** | [Download](https://huggingface.co/CyberHarem/dagda_arknights/resolve/main/1287/dagda_arknights.zip) | ![pattern_0_0](1287/previews/pattern_0_0.png) | ![pattern_0_1](1287/previews/pattern_0_1.png) | ![pattern_1](1287/previews/pattern_1.png) | ![portrait_0](1287/previews/portrait_0.png) | ![portrait_1](1287/previews/portrait_1.png) | ![portrait_2](1287/previews/portrait_2.png) | ![full_body_0](1287/previews/full_body_0.png) | ![full_body_1](1287/previews/full_body_1.png) | ![profile_0](1287/previews/profile_0.png) | ![profile_1](1287/previews/profile_1.png) | ![free_0](1287/previews/free_0.png) | ![free_1](1287/previews/free_1.png) | ![shorts](1287/previews/shorts.png) | ![maid_0](1287/previews/maid_0.png) | ![maid_1](1287/previews/maid_1.png) | ![miko](1287/previews/miko.png) | ![yukata](1287/previews/yukata.png) | ![suit](1287/previews/suit.png) | ![china](1287/previews/china.png) | ![bikini_0](1287/previews/bikini_0.png) | ![bikini_1](1287/previews/bikini_1.png) | ![bikini_2](1287/previews/bikini_2.png) | ![sit](1287/previews/sit.png) | ![squat](1287/previews/squat.png) | ![kneel](1287/previews/kneel.png) | ![jump](1287/previews/jump.png) | ![crossed_arms](1287/previews/crossed_arms.png) | ![angry](1287/previews/angry.png) | ![smile](1287/previews/smile.png) | ![cry](1287/previews/cry.png) | ![grin](1287/previews/grin.png) | ![n_lie_0](1287/previews/n_lie_0.png) | ![n_lie_1](1287/previews/n_lie_1.png) | ![n_stand_0](1287/previews/n_stand_0.png) | ![n_stand_1](1287/previews/n_stand_1.png) | ![n_stand_2](1287/previews/n_stand_2.png) | ![n_sex_0](1287/previews/n_sex_0.png) | ![n_sex_1](1287/previews/n_sex_1.png) |
| 1485 | 45 | 0.959 | 0.989 | 0.847 | 0.861 | [Download](https://huggingface.co/CyberHarem/dagda_arknights/resolve/main/1485/dagda_arknights.zip) | ![pattern_0_0](1485/previews/pattern_0_0.png) | ![pattern_0_1](1485/previews/pattern_0_1.png) | ![pattern_1](1485/previews/pattern_1.png) | ![portrait_0](1485/previews/portrait_0.png) | ![portrait_1](1485/previews/portrait_1.png) | ![portrait_2](1485/previews/portrait_2.png) | ![full_body_0](1485/previews/full_body_0.png) | ![full_body_1](1485/previews/full_body_1.png) | ![profile_0](1485/previews/profile_0.png) | ![profile_1](1485/previews/profile_1.png) | ![free_0](1485/previews/free_0.png) | ![free_1](1485/previews/free_1.png) | ![shorts](1485/previews/shorts.png) | ![maid_0](1485/previews/maid_0.png) | ![maid_1](1485/previews/maid_1.png) | ![miko](1485/previews/miko.png) | ![yukata](1485/previews/yukata.png) | ![suit](1485/previews/suit.png) | ![china](1485/previews/china.png) | ![bikini_0](1485/previews/bikini_0.png) | ![bikini_1](1485/previews/bikini_1.png) | ![bikini_2](1485/previews/bikini_2.png) | ![sit](1485/previews/sit.png) | ![squat](1485/previews/squat.png) | ![kneel](1485/previews/kneel.png) | ![jump](1485/previews/jump.png) | ![crossed_arms](1485/previews/crossed_arms.png) | ![angry](1485/previews/angry.png) | ![smile](1485/previews/smile.png) | ![cry](1485/previews/cry.png) | ![grin](1485/previews/grin.png) | ![n_lie_0](1485/previews/n_lie_0.png) | ![n_lie_1](1485/previews/n_lie_1.png) | ![n_stand_0](1485/previews/n_stand_0.png) | ![n_stand_1](1485/previews/n_stand_1.png) | ![n_stand_2](1485/previews/n_stand_2.png) | ![n_sex_0](1485/previews/n_sex_0.png) | ![n_sex_1](1485/previews/n_sex_1.png) |
| 1188 | 36 | 0.951 | 0.992 | 0.849 | 0.791 | [Download](https://huggingface.co/CyberHarem/dagda_arknights/resolve/main/1188/dagda_arknights.zip) | ![pattern_0_0](1188/previews/pattern_0_0.png) | ![pattern_0_1](1188/previews/pattern_0_1.png) | ![pattern_1](1188/previews/pattern_1.png) | ![portrait_0](1188/previews/portrait_0.png) | ![portrait_1](1188/previews/portrait_1.png) | ![portrait_2](1188/previews/portrait_2.png) | ![full_body_0](1188/previews/full_body_0.png) | ![full_body_1](1188/previews/full_body_1.png) | ![profile_0](1188/previews/profile_0.png) | ![profile_1](1188/previews/profile_1.png) | ![free_0](1188/previews/free_0.png) | ![free_1](1188/previews/free_1.png) | ![shorts](1188/previews/shorts.png) | ![maid_0](1188/previews/maid_0.png) | ![maid_1](1188/previews/maid_1.png) | ![miko](1188/previews/miko.png) | ![yukata](1188/previews/yukata.png) | ![suit](1188/previews/suit.png) | ![china](1188/previews/china.png) | ![bikini_0](1188/previews/bikini_0.png) | ![bikini_1](1188/previews/bikini_1.png) | ![bikini_2](1188/previews/bikini_2.png) | ![sit](1188/previews/sit.png) | ![squat](1188/previews/squat.png) | ![kneel](1188/previews/kneel.png) | ![jump](1188/previews/jump.png) | ![crossed_arms](1188/previews/crossed_arms.png) | ![angry](1188/previews/angry.png) | ![smile](1188/previews/smile.png) | ![cry](1188/previews/cry.png) | ![grin](1188/previews/grin.png) | ![n_lie_0](1188/previews/n_lie_0.png) | ![n_lie_1](1188/previews/n_lie_1.png) | ![n_stand_0](1188/previews/n_stand_0.png) | ![n_stand_1](1188/previews/n_stand_1.png) | ![n_stand_2](1188/previews/n_stand_2.png) | ![n_sex_0](1188/previews/n_sex_0.png) | ![n_sex_1](1188/previews/n_sex_1.png) |
| 2574 | 78 | 0.952 | 0.977 | 0.840 | 0.778 | [Download](https://huggingface.co/CyberHarem/dagda_arknights/resolve/main/2574/dagda_arknights.zip) | ![pattern_0_0](2574/previews/pattern_0_0.png) | ![pattern_0_1](2574/previews/pattern_0_1.png) | ![pattern_1](2574/previews/pattern_1.png) | ![portrait_0](2574/previews/portrait_0.png) | ![portrait_1](2574/previews/portrait_1.png) | ![portrait_2](2574/previews/portrait_2.png) | ![full_body_0](2574/previews/full_body_0.png) | ![full_body_1](2574/previews/full_body_1.png) | ![profile_0](2574/previews/profile_0.png) | ![profile_1](2574/previews/profile_1.png) | ![free_0](2574/previews/free_0.png) | ![free_1](2574/previews/free_1.png) | ![shorts](2574/previews/shorts.png) | ![maid_0](2574/previews/maid_0.png) | ![maid_1](2574/previews/maid_1.png) | ![miko](2574/previews/miko.png) | ![yukata](2574/previews/yukata.png) | ![suit](2574/previews/suit.png) | ![china](2574/previews/china.png) | ![bikini_0](2574/previews/bikini_0.png) | ![bikini_1](2574/previews/bikini_1.png) | ![bikini_2](2574/previews/bikini_2.png) | ![sit](2574/previews/sit.png) | ![squat](2574/previews/squat.png) | ![kneel](2574/previews/kneel.png) | ![jump](2574/previews/jump.png) | ![crossed_arms](2574/previews/crossed_arms.png) | ![angry](2574/previews/angry.png) | ![smile](2574/previews/smile.png) | ![cry](2574/previews/cry.png) | ![grin](2574/previews/grin.png) | ![n_lie_0](2574/previews/n_lie_0.png) | ![n_lie_1](2574/previews/n_lie_1.png) | ![n_stand_0](2574/previews/n_stand_0.png) | ![n_stand_1](2574/previews/n_stand_1.png) | ![n_stand_2](2574/previews/n_stand_2.png) | ![n_sex_0](2574/previews/n_sex_0.png) | ![n_sex_1](2574/previews/n_sex_1.png) |
| 297 | 9 | 0.949 | **0.995** | **0.853** | 0.778 | [Download](https://huggingface.co/CyberHarem/dagda_arknights/resolve/main/297/dagda_arknights.zip) | ![pattern_0_0](297/previews/pattern_0_0.png) | ![pattern_0_1](297/previews/pattern_0_1.png) | ![pattern_1](297/previews/pattern_1.png) | ![portrait_0](297/previews/portrait_0.png) | ![portrait_1](297/previews/portrait_1.png) | ![portrait_2](297/previews/portrait_2.png) | ![full_body_0](297/previews/full_body_0.png) | ![full_body_1](297/previews/full_body_1.png) | ![profile_0](297/previews/profile_0.png) | ![profile_1](297/previews/profile_1.png) | ![free_0](297/previews/free_0.png) | ![free_1](297/previews/free_1.png) | ![shorts](297/previews/shorts.png) | ![maid_0](297/previews/maid_0.png) | ![maid_1](297/previews/maid_1.png) | ![miko](297/previews/miko.png) | ![yukata](297/previews/yukata.png) | ![suit](297/previews/suit.png) | ![china](297/previews/china.png) | ![bikini_0](297/previews/bikini_0.png) | ![bikini_1](297/previews/bikini_1.png) | ![bikini_2](297/previews/bikini_2.png) | ![sit](297/previews/sit.png) | ![squat](297/previews/squat.png) | ![kneel](297/previews/kneel.png) | ![jump](297/previews/jump.png) | ![crossed_arms](297/previews/crossed_arms.png) | ![angry](297/previews/angry.png) | ![smile](297/previews/smile.png) | ![cry](297/previews/cry.png) | ![grin](297/previews/grin.png) | ![n_lie_0](297/previews/n_lie_0.png) | ![n_lie_1](297/previews/n_lie_1.png) | ![n_stand_0](297/previews/n_stand_0.png) | ![n_stand_1](297/previews/n_stand_1.png) | ![n_stand_2](297/previews/n_stand_2.png) | ![n_sex_0](297/previews/n_sex_0.png) | ![n_sex_1](297/previews/n_sex_1.png) |
## Anything Else?
Because the automation of LoRA training always annoys some people. So for the following groups, it is not recommended to use this model and we express regret:
1. Individuals who cannot tolerate any deviations from the original character design, even in the slightest detail.
2. Individuals who are facing the application scenarios with high demands for accuracy in recreating character outfits.
3. Individuals who cannot accept the potential randomness in AI-generated images based on the Stable Diffusion algorithm.
4. Individuals who are not comfortable with the fully automated process of training character models using LoRA, or those who believe that training character models must be done purely through manual operations to avoid disrespecting the characters.
5. Individuals who finds the generated image content offensive to their values.
## All Steps
We uploaded the files in all steps. you can check the images, metrics and download them in the following links:
* [Steps From 1782 to 2640](all/0.md)
* [Steps From 792 to 1683](all/1.md)
* [Steps From 99 to 693](all/2.md)
|
Bruh110/omahlayai | Bruh110 | "2024-02-03T01:27:19Z" | 0 | 0 | null | [
"license:openrail",
"region:us"
] | null | "2024-02-03T01:26:20Z" | ---
license: openrail
---
|
rclonediego/fs | rclonediego | "2024-02-03T01:27:14Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-02-03T01:26:37Z" | Entry not found |
9duALEX/Abuelo | 9duALEX | "2024-02-03T01:28:17Z" | 0 | 0 | null | [
"license:openrail",
"region:us"
] | null | "2024-02-03T01:27:01Z" | ---
license: openrail
---
|
daquarti/zephyr-7b-sft-lora | daquarti | "2024-02-06T18:32:57Z" | 0 | 0 | null | [
"tensorboard",
"safetensors",
"trl",
"sft",
"generated_from_trainer",
"dataset:generator",
"base_model:mistralai/Mistral-7B-v0.1",
"base_model:finetune:mistralai/Mistral-7B-v0.1",
"license:apache-2.0",
"region:us"
] | null | "2024-02-03T01:27:29Z" | ---
license: apache-2.0
base_model: mistralai/Mistral-7B-v0.1
tags:
- trl
- sft
- generated_from_trainer
datasets:
- generator
model-index:
- name: zephyr-7b-sft-lora
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. -->
# zephyr-7b-sft-lora
This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the generator dataset.
## 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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 128
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log | 1.0 | 1 | 1.1586 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
|
Awais12/test | Awais12 | "2024-02-03T01:27:57Z" | 0 | 0 | null | [
"license:mit",
"region:us"
] | null | "2024-02-03T01:27:57Z" | ---
license: mit
---
|
rauleeto/my_awesome_wnut_model | rauleeto | "2024-02-03T01:29:00Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-02-03T01:29:00Z" | Entry not found |
r3m3c3/english-to-kanji-c44500_model_3_v_0 | r3m3c3 | "2024-02-03T01:30:19Z" | 0 | 0 | diffusers | [
"diffusers",
"safetensors",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | "2024-02-03T01:29:11Z" | ---
library_name: diffusers
---
# 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 🧨 diffusers 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]
|
modeldodel/HEEJIN | modeldodel | "2024-02-03T01:30:48Z" | 0 | 0 | null | [
"license:openrail",
"region:us"
] | null | "2024-02-03T01:29:19Z" | ---
license: openrail
---
|
r3m3c3/english-to-kanji-c46000_model_3_v_0 | r3m3c3 | "2024-02-03T01:32:01Z" | 0 | 0 | diffusers | [
"diffusers",
"safetensors",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | "2024-02-03T01:30:42Z" | ---
library_name: diffusers
---
# 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 🧨 diffusers 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]
|
r3m3c3/english-to-kanji-c47500_model_3_v_0 | r3m3c3 | "2024-02-03T01:32:49Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-02-03T01:32:48Z" | Entry not found |
PierreCounathe/Reinforce-Pixelcopter-PLE-v0 | PierreCounathe | "2024-02-10T01:44:03Z" | 0 | 0 | null | [
"Pixelcopter-PLE-v0",
"reinforce",
"reinforcement-learning",
"custom-implementation",
"deep-rl-class",
"model-index",
"region:us"
] | reinforcement-learning | "2024-02-03T01:47:44Z" | ---
tags:
- Pixelcopter-PLE-v0
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: Reinforce-Pixelcopter-PLE-v0
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Pixelcopter-PLE-v0
type: Pixelcopter-PLE-v0
metrics:
- type: mean_reward
value: 34.30 +/- 25.55
name: mean_reward
verified: false
---
# **Reinforce** Agent playing **Pixelcopter-PLE-v0**
This is a trained model of a **Reinforce** agent playing **Pixelcopter-PLE-v0** .
To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: https://huggingface.co/deep-rl-course/unit4/introduction
|
BillD/llama-7b-qlora-ultrachat | BillD | "2024-02-03T05:10:05Z" | 0 | 0 | null | [
"tensorboard",
"safetensors",
"region:us"
] | null | "2024-02-03T01:53:52Z" | Entry not found |
vilm/Quyen-Mini-4e | vilm | "2024-02-03T02:08:02Z" | 0 | 0 | transformers | [
"transformers",
"pytorch",
"safetensors",
"qwen2",
"text-generation",
"generated_from_trainer",
"conversational",
"base_model:Qwen/Qwen1.5-1.8B",
"base_model:finetune:Qwen/Qwen1.5-1.8B",
"license:other",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | "2024-02-03T02:07:20Z" | ---
license: other
base_model: Qwen/Qwen2-beta-1_8B
tags:
- generated_from_trainer
model-index:
- name: quyen-1_8b
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. -->
[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
<details><summary>See axolotl config</summary>
axolotl version: `0.4.0`
```yaml
base_model: Qwen/Qwen2-beta-1_8B
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer
is_qwen_derived_model:
trust_remote_code:
load_in_8bit: false
load_in_4bit: false
strict: false
datasets:
- path: teknium/OpenHermes-2.5
type: sharegpt
conversation: chatml
dataset_prepared_path: last_run_prepared
val_set_size: 0.0
output_dir: ./quyen-1_8b
sequence_len: 4096 # supports up to 8192
sample_packing: true
pad_to_sequence_len: true
adapter:
lora_model_dir:
lora_r:
lora_alpha:
lora_dropout:
lora_target_linear:
lora_fan_in_fan_out:
wandb_project: quyen-hermes
wandb_entity:
wandb_watch:
wandb_name: quyen-1_8b-hermes
wandb_log_model:
gradient_accumulation_steps: 8
micro_batch_size: 8
num_epochs: 4
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 0.0001
train_on_inputs: false
group_by_length: false
bf16: true
fp16:
tf32: false
gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true
warmup_steps: 10
evals_per_epoch:
eval_table_size:
eval_table_max_new_tokens:
saves_per_epoch: 1
debug:
deepspeed: deepspeed_configs/zero3_bf16.json
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:
eos_token: "<|im_end|>"
tokens:
- "<|im_start|>"
```
</details><br>
# quyen-1_8b
This model is a fine-tuned version of [Qwen/Qwen2-beta-1_8B](https://huggingface.co/Qwen/Qwen2-beta-1_8B) on the None dataset.
## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 8
- total_train_batch_size: 256
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 4
### Training results
### Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0
|
XinHun/YD_JQS | XinHun | "2024-02-03T02:22:24Z" | 0 | 0 | null | [
"license:other",
"region:us"
] | null | "2024-02-03T02:20:35Z" | ---
license: other
license_name: '1'
license_link: LICENSE
---
|
TheLifey/cabal | TheLifey | "2024-02-26T23:56:12Z" | 0 | 1 | null | [
"en",
"region:us"
] | null | "2024-02-03T02:26:54Z" | ---
language:
- en
--- |
niharikabalachandra/flowers_classification | niharikabalachandra | "2024-02-04T00:57:43Z" | 0 | 0 | null | [
"license:apache-2.0",
"region:us"
] | null | "2024-02-03T02:30:39Z" | ---
license: apache-2.0
---
|
TH78/pamelacorbett | TH78 | "2024-02-03T02:35:20Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-02-03T02:32:23Z" | Entry not found |
bart-automation/sft_zephyr | bart-automation | "2024-02-03T02:34:38Z" | 0 | 0 | peft | [
"peft",
"tensorboard",
"safetensors",
"trl",
"sft",
"generated_from_trainer",
"base_model:HuggingFaceH4/zephyr-7b-alpha",
"base_model:adapter:HuggingFaceH4/zephyr-7b-alpha",
"license:mit",
"region:us"
] | null | "2024-02-03T02:34:23Z" | ---
license: mit
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: HuggingFaceH4/zephyr-7b-alpha
model-index:
- name: sft_zephyr
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. -->
# sft_zephyr
This model is a fine-tuned version of [HuggingFaceH4/zephyr-7b-alpha](https://huggingface.co/HuggingFaceH4/zephyr-7b-alpha) on an unknown dataset.
## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 5
### Training results
### Framework versions
- PEFT 0.8.2
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1 |
rafaeljuniorvip/liberado | rafaeljuniorvip | "2024-02-03T02:40:16Z" | 0 | 0 | null | [
"license:apache-2.0",
"region:us"
] | null | "2024-02-03T02:40:16Z" | ---
license: apache-2.0
---
|
jbuch808/sac-PandaPickAndPlace-v3 | jbuch808 | "2024-02-03T02:47:24Z" | 0 | 0 | stable-baselines3 | [
"stable-baselines3",
"PandaPickAndPlace-v3",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | reinforcement-learning | "2024-02-03T02:46:07Z" | ---
library_name: stable-baselines3
tags:
- PandaPickAndPlace-v3
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: SAC
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: PandaPickAndPlace-v3
type: PandaPickAndPlace-v3
metrics:
- type: mean_reward
value: -50.00 +/- 0.00
name: mean_reward
verified: false
---
# **SAC** Agent playing **PandaPickAndPlace-v3**
This is a trained model of a **SAC** agent playing **PandaPickAndPlace-v3**
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
...
```
|
Inktactile1123/davemustainesmooth | Inktactile1123 | "2024-02-03T02:50:19Z" | 0 | 0 | null | [
"license:apache-2.0",
"region:us"
] | null | "2024-02-03T02:49:14Z" | ---
license: apache-2.0
---
|
hepp/Bomman | hepp | "2024-02-03T03:11:08Z" | 0 | 0 | null | [
"license:apache-2.0",
"region:us"
] | null | "2024-02-03T02:49:31Z" | ---
license: apache-2.0
---
|
tsk-18/model-1 | tsk-18 | "2024-02-03T02:55:57Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-02-03T02:55:56Z" | Entry not found |
kawaiigirlsz045/DayaneRamos | kawaiigirlsz045 | "2024-02-03T02:57:41Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-02-03T02:57:09Z" | Entry not found |
AiHubber/MindplayLady1 | AiHubber | "2024-02-03T03:01:04Z" | 0 | 0 | null | [
"license:openrail",
"region:us"
] | null | "2024-02-03T03:00:12Z" | ---
license: openrail
---
|
metalwhale/jina-embeddings-v2-base-en-ft | metalwhale | "2024-02-03T03:04:12Z" | 0 | 0 | null | [
"safetensors",
"license:apache-2.0",
"region:us"
] | null | "2024-02-03T03:03:38Z" | ---
license: apache-2.0
---
|
hjhkoream/whisper_small_copy | hjhkoream | "2024-02-06T08:23:14Z" | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"whisper",
"automatic-speech-recognition",
"hf-asr-leaderboard",
"generated_from_trainer",
"hi",
"dataset:mozilla-foundation/common_voice_11_0",
"base_model:openai/whisper-small",
"base_model:finetune:openai/whisper-small",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | automatic-speech-recognition | "2024-02-03T03:05:29Z" | ---
language:
- hi
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
model-index:
- name: Whisper Small Hi - Sanchit Gandhi
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. -->
# Whisper Small Hi - Sanchit Gandhi
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset.
## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
### Framework versions
- Transformers 4.37.1
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.1
|
YurkiSan/Barrinha2.0 | YurkiSan | "2024-02-03T03:08:08Z" | 0 | 0 | null | [
"license:openrail",
"region:us"
] | null | "2024-02-03T03:07:16Z" | ---
license: openrail
---
|
oiuoiuoi/xxmix | oiuoiuoi | "2024-02-04T01:18:02Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-02-03T03:07:20Z" | Entry not found |
oiuoiuoi/xxmixlora | oiuoiuoi | "2024-02-04T07:51:30Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-02-03T03:07:53Z" | Entry not found |
Homiebear/HHAlastor | Homiebear | "2024-02-03T03:10:40Z" | 0 | 0 | null | [
"license:openrail",
"region:us"
] | null | "2024-02-03T03:10:38Z" | ---
license: openrail
---
|
haoheliu/audiosr_basic | haoheliu | "2024-02-03T10:17:52Z" | 0 | 0 | null | [
"pytorch",
"license:apache-2.0",
"region:us"
] | null | "2024-02-03T03:12:54Z" | ---
license: apache-2.0
---
|
haoheliu/audiosr_speech | haoheliu | "2024-02-03T03:49:12Z" | 0 | 0 | null | [
"pytorch",
"region:us"
] | null | "2024-02-03T03:13:04Z" | Entry not found |
hanoseok/melissa-model | hanoseok | "2024-02-03T03:25:15Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-02-03T03:25:15Z" | Entry not found |
dengh/a2c-PandaReachDense-v3 | dengh | "2024-02-03T03:36:06Z" | 0 | 0 | stable-baselines3 | [
"stable-baselines3",
"PandaReachDense-v3",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | reinforcement-learning | "2024-02-03T03:28:08Z" | ---
library_name: stable-baselines3
tags:
- PandaReachDense-v3
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: A2C
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: PandaReachDense-v3
type: PandaReachDense-v3
metrics:
- type: mean_reward
value: -0.23 +/- 0.14
name: mean_reward
verified: false
---
# **A2C** Agent playing **PandaReachDense-v3**
This is a trained model of a **A2C** agent playing **PandaReachDense-v3**
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
...
```
|
CyberHarem/michiru_kinushima_plasticmemories | CyberHarem | "2024-02-03T03:40:22Z" | 0 | 0 | null | [
"art",
"not-for-all-audiences",
"text-to-image",
"dataset:CyberHarem/michiru_kinushima_plasticmemories",
"dataset:BangumiBase/plasticmemories",
"license:mit",
"region:us"
] | text-to-image | "2024-02-03T03:29:12Z" | ---
license: mit
datasets:
- CyberHarem/michiru_kinushima_plasticmemories
- BangumiBase/plasticmemories
pipeline_tag: text-to-image
tags:
- art
- not-for-all-audiences
---
# Lora of Michiru Kinushima (Plastic Memories)
## What Is This?
This is the LoRA model of waifu Michiru Kinushima (Plastic Memories).
## How Is It Trained?
* This model is trained with [HCP-Diffusion](https://github.com/7eu7d7/HCP-Diffusion).
* The [auto-training framework](https://github.com/deepghs/cyberharem) is maintained by [DeepGHS Team](https://huggingface.co/deepghs).
* The base model used for training is [deepghs/animefull-latest](https://huggingface.co/deepghs/animefull-latest).
* Dataset used for training is the `stage3-p480-800` in [CyberHarem/michiru_kinushima_plasticmemories](https://huggingface.co/datasets/CyberHarem/michiru_kinushima_plasticmemories), which contains 347 images.
* The images in the dataset is auto-cropped from anime videos, more images for other waifus in the same anime can be found in [BangumiBase/plasticmemories](https://huggingface.co/datasets/BangumiBase/plasticmemories)
* Batch size is 4, resolution is 720x720, clustering into 5 buckets.
* Batch size for regularization dataset is 10, resolution is 720x720, clustering into 10 buckets.
* Trained for 3480 steps, 40 checkpoints were saved and evaluated.
* **Trigger word is `michiru_kinushima_plasticmemories`.**
* Pruned core tags for this waifu are `orange_hair, long_hair, blue_eyes, bangs`. You can add them to the prompt when some features of waifu (e.g. hair color) are not stable.
## How to Use It?
### If You Are Using A1111 WebUI v1.7+
**Just use it like the classic LoRA**. The LoRA we provided are bundled with the embedding file.
### If You Are Using A1111 WebUI v1.6 or Lower
After downloading the pt and safetensors files for the specified step, you need to use them simultaneously. The pt file will be used as an embedding, while the safetensors file will be loaded for Lora.
For example, if you want to use the model from step 2349, you need to download [`2349/michiru_kinushima_plasticmemories.pt`](https://huggingface.co/CyberHarem/michiru_kinushima_plasticmemories/resolve/main/2349/michiru_kinushima_plasticmemories.pt) as the embedding and [`2349/michiru_kinushima_plasticmemories.safetensors`](https://huggingface.co/CyberHarem/michiru_kinushima_plasticmemories/resolve/main/2349/michiru_kinushima_plasticmemories.safetensors) for loading Lora. By using both files together, you can generate images for the desired characters.
## Which Step Should I Use?
We selected 5 good steps for you to choose. The best one is step 2349.
1680 images (1.58 GiB) were generated for auto-testing.
![Metrics Plot](metrics_plot.png)
The base model used for generating preview images is [Meina/MeinaMix_V11](https://huggingface.co/Meina/MeinaMix_V11).
Here are the preview of the recommended steps:
| Step | Epoch | CCIP | AI Corrupt | Bikini Plus | Score | Download | pattern_0_0 | pattern_0_1 | pattern_0_2 | pattern_1 | pattern_2_0 | pattern_2_1 | pattern_3 | portrait_0 | portrait_1 | portrait_2 | full_body_0 | full_body_1 | profile_0 | profile_1 | free_0 | free_1 | shorts | maid_0 | maid_1 | miko | yukata | suit | china | bikini_0 | bikini_1 | bikini_2 | sit | squat | kneel | jump | crossed_arms | angry | smile | cry | grin | n_lie_0 | n_lie_1 | n_stand_0 | n_stand_1 | n_stand_2 | n_sex_0 | n_sex_1 |
|-------:|--------:|:----------|:-------------|:--------------|:----------|:----------------------------------------------------------------------------------------------------------------------------------------|:----------------------------------------------|:----------------------------------------------|:----------------------------------------------|:------------------------------------------|:----------------------------------------------|:----------------------------------------------|:------------------------------------------|:--------------------------------------------|:--------------------------------------------|:--------------------------------------------|:----------------------------------------------|:----------------------------------------------|:------------------------------------------|:------------------------------------------|:------------------------------------|:------------------------------------|:------------------------------------|:------------------------------------|:------------------------------------|:--------------------------------|:------------------------------------|:--------------------------------|:----------------------------------|:----------------------------------------|:----------------------------------------|:----------------------------------------|:------------------------------|:----------------------------------|:----------------------------------|:--------------------------------|:------------------------------------------------|:----------------------------------|:----------------------------------|:------------------------------|:--------------------------------|:--------------------------------------|:--------------------------------------|:------------------------------------------|:------------------------------------------|:------------------------------------------|:--------------------------------------|:--------------------------------------|
| 2349 | 28 | 0.930 | 0.850 | 0.834 | **0.763** | [Download](https://huggingface.co/CyberHarem/michiru_kinushima_plasticmemories/resolve/main/2349/michiru_kinushima_plasticmemories.zip) | ![pattern_0_0](2349/previews/pattern_0_0.png) | ![pattern_0_1](2349/previews/pattern_0_1.png) | ![pattern_0_2](2349/previews/pattern_0_2.png) | ![pattern_1](2349/previews/pattern_1.png) | ![pattern_2_0](2349/previews/pattern_2_0.png) | ![pattern_2_1](2349/previews/pattern_2_1.png) | ![pattern_3](2349/previews/pattern_3.png) | ![portrait_0](2349/previews/portrait_0.png) | ![portrait_1](2349/previews/portrait_1.png) | ![portrait_2](2349/previews/portrait_2.png) | ![full_body_0](2349/previews/full_body_0.png) | ![full_body_1](2349/previews/full_body_1.png) | ![profile_0](2349/previews/profile_0.png) | ![profile_1](2349/previews/profile_1.png) | ![free_0](2349/previews/free_0.png) | ![free_1](2349/previews/free_1.png) | ![shorts](2349/previews/shorts.png) | ![maid_0](2349/previews/maid_0.png) | ![maid_1](2349/previews/maid_1.png) | ![miko](2349/previews/miko.png) | ![yukata](2349/previews/yukata.png) | ![suit](2349/previews/suit.png) | ![china](2349/previews/china.png) | ![bikini_0](2349/previews/bikini_0.png) | ![bikini_1](2349/previews/bikini_1.png) | ![bikini_2](2349/previews/bikini_2.png) | ![sit](2349/previews/sit.png) | ![squat](2349/previews/squat.png) | ![kneel](2349/previews/kneel.png) | ![jump](2349/previews/jump.png) | ![crossed_arms](2349/previews/crossed_arms.png) | ![angry](2349/previews/angry.png) | ![smile](2349/previews/smile.png) | ![cry](2349/previews/cry.png) | ![grin](2349/previews/grin.png) | ![n_lie_0](2349/previews/n_lie_0.png) | ![n_lie_1](2349/previews/n_lie_1.png) | ![n_stand_0](2349/previews/n_stand_0.png) | ![n_stand_1](2349/previews/n_stand_1.png) | ![n_stand_2](2349/previews/n_stand_2.png) | ![n_sex_0](2349/previews/n_sex_0.png) | ![n_sex_1](2349/previews/n_sex_1.png) |
| 1914 | 23 | **0.932** | **0.938** | 0.828 | 0.754 | [Download](https://huggingface.co/CyberHarem/michiru_kinushima_plasticmemories/resolve/main/1914/michiru_kinushima_plasticmemories.zip) | ![pattern_0_0](1914/previews/pattern_0_0.png) | ![pattern_0_1](1914/previews/pattern_0_1.png) | ![pattern_0_2](1914/previews/pattern_0_2.png) | ![pattern_1](1914/previews/pattern_1.png) | ![pattern_2_0](1914/previews/pattern_2_0.png) | ![pattern_2_1](1914/previews/pattern_2_1.png) | ![pattern_3](1914/previews/pattern_3.png) | ![portrait_0](1914/previews/portrait_0.png) | ![portrait_1](1914/previews/portrait_1.png) | ![portrait_2](1914/previews/portrait_2.png) | ![full_body_0](1914/previews/full_body_0.png) | ![full_body_1](1914/previews/full_body_1.png) | ![profile_0](1914/previews/profile_0.png) | ![profile_1](1914/previews/profile_1.png) | ![free_0](1914/previews/free_0.png) | ![free_1](1914/previews/free_1.png) | ![shorts](1914/previews/shorts.png) | ![maid_0](1914/previews/maid_0.png) | ![maid_1](1914/previews/maid_1.png) | ![miko](1914/previews/miko.png) | ![yukata](1914/previews/yukata.png) | ![suit](1914/previews/suit.png) | ![china](1914/previews/china.png) | ![bikini_0](1914/previews/bikini_0.png) | ![bikini_1](1914/previews/bikini_1.png) | ![bikini_2](1914/previews/bikini_2.png) | ![sit](1914/previews/sit.png) | ![squat](1914/previews/squat.png) | ![kneel](1914/previews/kneel.png) | ![jump](1914/previews/jump.png) | ![crossed_arms](1914/previews/crossed_arms.png) | ![angry](1914/previews/angry.png) | ![smile](1914/previews/smile.png) | ![cry](1914/previews/cry.png) | ![grin](1914/previews/grin.png) | ![n_lie_0](1914/previews/n_lie_0.png) | ![n_lie_1](1914/previews/n_lie_1.png) | ![n_stand_0](1914/previews/n_stand_0.png) | ![n_stand_1](1914/previews/n_stand_1.png) | ![n_stand_2](1914/previews/n_stand_2.png) | ![n_sex_0](1914/previews/n_sex_0.png) | ![n_sex_1](1914/previews/n_sex_1.png) |
| 2958 | 35 | 0.914 | 0.857 | 0.831 | 0.739 | [Download](https://huggingface.co/CyberHarem/michiru_kinushima_plasticmemories/resolve/main/2958/michiru_kinushima_plasticmemories.zip) | ![pattern_0_0](2958/previews/pattern_0_0.png) | ![pattern_0_1](2958/previews/pattern_0_1.png) | ![pattern_0_2](2958/previews/pattern_0_2.png) | ![pattern_1](2958/previews/pattern_1.png) | ![pattern_2_0](2958/previews/pattern_2_0.png) | ![pattern_2_1](2958/previews/pattern_2_1.png) | ![pattern_3](2958/previews/pattern_3.png) | ![portrait_0](2958/previews/portrait_0.png) | ![portrait_1](2958/previews/portrait_1.png) | ![portrait_2](2958/previews/portrait_2.png) | ![full_body_0](2958/previews/full_body_0.png) | ![full_body_1](2958/previews/full_body_1.png) | ![profile_0](2958/previews/profile_0.png) | ![profile_1](2958/previews/profile_1.png) | ![free_0](2958/previews/free_0.png) | ![free_1](2958/previews/free_1.png) | ![shorts](2958/previews/shorts.png) | ![maid_0](2958/previews/maid_0.png) | ![maid_1](2958/previews/maid_1.png) | ![miko](2958/previews/miko.png) | ![yukata](2958/previews/yukata.png) | ![suit](2958/previews/suit.png) | ![china](2958/previews/china.png) | ![bikini_0](2958/previews/bikini_0.png) | ![bikini_1](2958/previews/bikini_1.png) | ![bikini_2](2958/previews/bikini_2.png) | ![sit](2958/previews/sit.png) | ![squat](2958/previews/squat.png) | ![kneel](2958/previews/kneel.png) | ![jump](2958/previews/jump.png) | ![crossed_arms](2958/previews/crossed_arms.png) | ![angry](2958/previews/angry.png) | ![smile](2958/previews/smile.png) | ![cry](2958/previews/cry.png) | ![grin](2958/previews/grin.png) | ![n_lie_0](2958/previews/n_lie_0.png) | ![n_lie_1](2958/previews/n_lie_1.png) | ![n_stand_0](2958/previews/n_stand_0.png) | ![n_stand_1](2958/previews/n_stand_1.png) | ![n_stand_2](2958/previews/n_stand_2.png) | ![n_sex_0](2958/previews/n_sex_0.png) | ![n_sex_1](2958/previews/n_sex_1.png) |
| 1740 | 21 | 0.902 | 0.893 | **0.839** | 0.735 | [Download](https://huggingface.co/CyberHarem/michiru_kinushima_plasticmemories/resolve/main/1740/michiru_kinushima_plasticmemories.zip) | ![pattern_0_0](1740/previews/pattern_0_0.png) | ![pattern_0_1](1740/previews/pattern_0_1.png) | ![pattern_0_2](1740/previews/pattern_0_2.png) | ![pattern_1](1740/previews/pattern_1.png) | ![pattern_2_0](1740/previews/pattern_2_0.png) | ![pattern_2_1](1740/previews/pattern_2_1.png) | ![pattern_3](1740/previews/pattern_3.png) | ![portrait_0](1740/previews/portrait_0.png) | ![portrait_1](1740/previews/portrait_1.png) | ![portrait_2](1740/previews/portrait_2.png) | ![full_body_0](1740/previews/full_body_0.png) | ![full_body_1](1740/previews/full_body_1.png) | ![profile_0](1740/previews/profile_0.png) | ![profile_1](1740/previews/profile_1.png) | ![free_0](1740/previews/free_0.png) | ![free_1](1740/previews/free_1.png) | ![shorts](1740/previews/shorts.png) | ![maid_0](1740/previews/maid_0.png) | ![maid_1](1740/previews/maid_1.png) | ![miko](1740/previews/miko.png) | ![yukata](1740/previews/yukata.png) | ![suit](1740/previews/suit.png) | ![china](1740/previews/china.png) | ![bikini_0](1740/previews/bikini_0.png) | ![bikini_1](1740/previews/bikini_1.png) | ![bikini_2](1740/previews/bikini_2.png) | ![sit](1740/previews/sit.png) | ![squat](1740/previews/squat.png) | ![kneel](1740/previews/kneel.png) | ![jump](1740/previews/jump.png) | ![crossed_arms](1740/previews/crossed_arms.png) | ![angry](1740/previews/angry.png) | ![smile](1740/previews/smile.png) | ![cry](1740/previews/cry.png) | ![grin](1740/previews/grin.png) | ![n_lie_0](1740/previews/n_lie_0.png) | ![n_lie_1](1740/previews/n_lie_1.png) | ![n_stand_0](1740/previews/n_stand_0.png) | ![n_stand_1](1740/previews/n_stand_1.png) | ![n_stand_2](1740/previews/n_stand_2.png) | ![n_sex_0](1740/previews/n_sex_0.png) | ![n_sex_1](1740/previews/n_sex_1.png) |
| 2436 | 29 | 0.906 | 0.904 | 0.834 | 0.734 | [Download](https://huggingface.co/CyberHarem/michiru_kinushima_plasticmemories/resolve/main/2436/michiru_kinushima_plasticmemories.zip) | ![pattern_0_0](2436/previews/pattern_0_0.png) | ![pattern_0_1](2436/previews/pattern_0_1.png) | ![pattern_0_2](2436/previews/pattern_0_2.png) | ![pattern_1](2436/previews/pattern_1.png) | ![pattern_2_0](2436/previews/pattern_2_0.png) | ![pattern_2_1](2436/previews/pattern_2_1.png) | ![pattern_3](2436/previews/pattern_3.png) | ![portrait_0](2436/previews/portrait_0.png) | ![portrait_1](2436/previews/portrait_1.png) | ![portrait_2](2436/previews/portrait_2.png) | ![full_body_0](2436/previews/full_body_0.png) | ![full_body_1](2436/previews/full_body_1.png) | ![profile_0](2436/previews/profile_0.png) | ![profile_1](2436/previews/profile_1.png) | ![free_0](2436/previews/free_0.png) | ![free_1](2436/previews/free_1.png) | ![shorts](2436/previews/shorts.png) | ![maid_0](2436/previews/maid_0.png) | ![maid_1](2436/previews/maid_1.png) | ![miko](2436/previews/miko.png) | ![yukata](2436/previews/yukata.png) | ![suit](2436/previews/suit.png) | ![china](2436/previews/china.png) | ![bikini_0](2436/previews/bikini_0.png) | ![bikini_1](2436/previews/bikini_1.png) | ![bikini_2](2436/previews/bikini_2.png) | ![sit](2436/previews/sit.png) | ![squat](2436/previews/squat.png) | ![kneel](2436/previews/kneel.png) | ![jump](2436/previews/jump.png) | ![crossed_arms](2436/previews/crossed_arms.png) | ![angry](2436/previews/angry.png) | ![smile](2436/previews/smile.png) | ![cry](2436/previews/cry.png) | ![grin](2436/previews/grin.png) | ![n_lie_0](2436/previews/n_lie_0.png) | ![n_lie_1](2436/previews/n_lie_1.png) | ![n_stand_0](2436/previews/n_stand_0.png) | ![n_stand_1](2436/previews/n_stand_1.png) | ![n_stand_2](2436/previews/n_stand_2.png) | ![n_sex_0](2436/previews/n_sex_0.png) | ![n_sex_1](2436/previews/n_sex_1.png) |
## Anything Else?
Because the automation of LoRA training always annoys some people. So for the following groups, it is not recommended to use this model and we express regret:
1. Individuals who cannot tolerate any deviations from the original character design, even in the slightest detail.
2. Individuals who are facing the application scenarios with high demands for accuracy in recreating character outfits.
3. Individuals who cannot accept the potential randomness in AI-generated images based on the Stable Diffusion algorithm.
4. Individuals who are not comfortable with the fully automated process of training character models using LoRA, or those who believe that training character models must be done purely through manual operations to avoid disrespecting the characters.
5. Individuals who finds the generated image content offensive to their values.
## All Steps
We uploaded the files in all steps. you can check the images, metrics and download them in the following links:
* [Steps From 2697 to 3480](all/0.md)
* [Steps From 1827 to 2610](all/1.md)
* [Steps From 957 to 1740](all/2.md)
* [Steps From 87 to 870](all/3.md)
|
Yarofa/model_pre_R3090_v17 | Yarofa | "2024-02-03T03:30:52Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-02-03T03:30:52Z" | Entry not found |
thayde/Ashley | thayde | "2024-02-03T03:45:00Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-02-03T03:43:08Z" | Entry not found |
Bruh110/SICKOMODEWAA | Bruh110 | "2024-02-03T03:46:48Z" | 0 | 0 | null | [
"license:openrail",
"region:us"
] | null | "2024-02-03T03:45:32Z" | ---
license: openrail
---
|
AdAstra1/q-FrozenLake-v1-4x4-noSlippery | AdAstra1 | "2024-02-03T04:00:53Z" | 0 | 0 | null | [
"FrozenLake-v1-4x4-no_slippery",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
] | reinforcement-learning | "2024-02-03T03:45:45Z" | ---
tags:
- FrozenLake-v1-4x4-no_slippery
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: q-FrozenLake-v1-4x4-noSlippery
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: FrozenLake-v1-4x4-no_slippery
type: FrozenLake-v1-4x4-no_slippery
metrics:
- type: mean_reward
value: 1.00 +/- 0.00
name: mean_reward
verified: false
---
# **Q-Learning** Agent playing1 **FrozenLake-v1**
This is a trained model of a **Q-Learning** agent playing **FrozenLake-v1** .
## Usage
```python
model = load_from_hub(repo_id="AdAstra1/q-FrozenLake-v1-4x4-noSlippery", filename="q-learning.pkl")
# Don't forget to check if you need to add additional attributes (is_slippery=False etc)
env = gym.make(model["env_id"])
```
|
Nicoli314/SK | Nicoli314 | "2024-02-03T03:51:44Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-02-03T03:46:39Z" | Entry not found |
a1030788/phi-2-GGUF | a1030788 | "2024-02-03T03:48:10Z" | 0 | 0 | null | [
"gguf",
"endpoints_compatible",
"region:us"
] | null | "2024-02-03T03:47:03Z" | Entry not found |
ambrosfitz/zephyr-history-chat-v2.0 | ambrosfitz | "2024-02-03T03:47:27Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-02-03T03:47:26Z" | Entry not found |
CannotFindObject/RAM_ONNX | CannotFindObject | "2024-02-03T04:08:51Z" | 0 | 0 | null | [
"onnx",
"license:apache-2.0",
"region:us"
] | null | "2024-02-03T03:48:26Z" | ---
license: apache-2.0
---
This is an onnx model from recognize-anything.
The original link is from: https://github.com/xinyu1205/recognize-anything
|
CyberHarem/frost_arknights | CyberHarem | "2024-03-26T02:13:37Z" | 0 | 0 | null | [
"art",
"not-for-all-audiences",
"text-to-image",
"dataset:CyberHarem/frost_arknights",
"license:mit",
"region:us"
] | text-to-image | "2024-02-03T03:49:05Z" | ---
license: mit
datasets:
- CyberHarem/frost_arknights
pipeline_tag: text-to-image
tags:
- art
- not-for-all-audiences
---
# LoRA model of frost/Frost/霜华 (Arknights)
## What Is This?
This is the LoRA model of waifu frost/Frost/霜华 (Arknights).
## How Is It Trained?
* This model is trained with [kohya-ss/sd-scripts](https://github.com/kohya-ss/sd-scripts), and the test images are generated with [a1111's webui](AUTOMATIC1111/stable-diffusion-webui) and [API sdk](https://github.com/mix1009/sdwebuiapi).
* The [auto-training framework](https://github.com/deepghs/cyberharem) is maintained by [DeepGHS Team](https://huggingface.co/deepghs).
The architecture of base model is is `SD1.5`.
* Dataset used for training is the `stage3-p480-1200` in [CyberHarem/frost_arknights](https://huggingface.co/datasets/CyberHarem/frost_arknights), which contains 72 images.
* **Trigger word is `frost_arknights`.**
* Pruned core tags for this waifu are `black hair, hat, short hair, breasts, large breasts, black headwear, blue eyes`. You can add them to the prompt when some features of waifu (e.g. hair color) are not stable.
* For more details in training, you can take a look at [training configuration file](https://huggingface.co/CyberHarem/frost_arknights/resolve/main/train.toml).
* For more details in LoRA, you can download it, and read the metadata with a1111's webui.
## How to Use It?
After downloading the safetensors files for the specified step, you need to use them like common LoRA.
* Recommended LoRA weight is 0.5-0.85.
* Recommended trigger word weight is 0.7-1.1.
For example, if you want to use the model from step 1980, you need to download [`1980/frost_arknights.safetensors`](https://huggingface.co/CyberHarem/frost_arknights/resolve/main/1980/frost_arknights.safetensors) as LoRA. By using this model, you can generate images for the desired characters.
## Which Step Should I Use?
We selected 5 good steps for you to choose. The best one is step 1980.
972 images (999.19 MiB) were generated for auto-testing.
![Metrics Plot](metrics_plot.png)
The base model used for generating preview images is [meinamix_v11](https://huggingface.co/meinamix_v11).
Here are the preview of the recommended steps:
| Step | Epoch | CCIP | AI Corrupt | Bikini Plus | Score | Download | pattern_0 | portrait_0 | portrait_1 | portrait_2 | full_body_0 | full_body_1 | profile_0 | profile_1 | free_0 | free_1 | shorts | maid_0 | maid_1 | miko | yukata | suit | china | bikini_0 | bikini_1 | bikini_2 | sit | squat | kneel | jump | crossed_arms | angry | smile | cry | grin | n_lie_0 | n_lie_1 | n_stand_0 | n_stand_1 | n_stand_2 | n_sex_0 | n_sex_1 |
|-------:|--------:|:----------|:-------------|:--------------|:----------|:----------------------------------------------------------------------------------------------------|:------------------------------------------|:--------------------------------------------|:--------------------------------------------|:--------------------------------------------|:----------------------------------------------|:----------------------------------------------|:------------------------------------------|:------------------------------------------|:------------------------------------|:------------------------------------|:------------------------------------|:------------------------------------|:------------------------------------|:--------------------------------|:------------------------------------|:--------------------------------|:----------------------------------|:----------------------------------------|:----------------------------------------|:----------------------------------------|:------------------------------|:----------------------------------|:----------------------------------|:--------------------------------|:------------------------------------------------|:----------------------------------|:----------------------------------|:------------------------------|:--------------------------------|:--------------------------------------|:--------------------------------------|:------------------------------------------|:------------------------------------------|:------------------------------------------|:--------------------------------------|:--------------------------------------|
| 1980 | 66 | **0.258** | 0.957 | 0.836 | **0.879** | [Download](https://huggingface.co/CyberHarem/frost_arknights/resolve/main/1980/frost_arknights.zip) | ![pattern_0](1980/previews/pattern_0.png) | ![portrait_0](1980/previews/portrait_0.png) | ![portrait_1](1980/previews/portrait_1.png) | ![portrait_2](1980/previews/portrait_2.png) | ![full_body_0](1980/previews/full_body_0.png) | ![full_body_1](1980/previews/full_body_1.png) | ![profile_0](1980/previews/profile_0.png) | ![profile_1](1980/previews/profile_1.png) | ![free_0](1980/previews/free_0.png) | ![free_1](1980/previews/free_1.png) | ![shorts](1980/previews/shorts.png) | ![maid_0](1980/previews/maid_0.png) | ![maid_1](1980/previews/maid_1.png) | ![miko](1980/previews/miko.png) | ![yukata](1980/previews/yukata.png) | ![suit](1980/previews/suit.png) | ![china](1980/previews/china.png) | ![bikini_0](1980/previews/bikini_0.png) | ![bikini_1](1980/previews/bikini_1.png) | ![bikini_2](1980/previews/bikini_2.png) | ![sit](1980/previews/sit.png) | ![squat](1980/previews/squat.png) | ![kneel](1980/previews/kneel.png) | ![jump](1980/previews/jump.png) | ![crossed_arms](1980/previews/crossed_arms.png) | ![angry](1980/previews/angry.png) | ![smile](1980/previews/smile.png) | ![cry](1980/previews/cry.png) | ![grin](1980/previews/grin.png) | ![n_lie_0](1980/previews/n_lie_0.png) | ![n_lie_1](1980/previews/n_lie_1.png) | ![n_stand_0](1980/previews/n_stand_0.png) | ![n_stand_1](1980/previews/n_stand_1.png) | ![n_stand_2](1980/previews/n_stand_2.png) | ![n_sex_0](1980/previews/n_sex_0.png) | ![n_sex_1](1980/previews/n_sex_1.png) |
| 1530 | 51 | 0.234 | 0.959 | **0.849** | 0.855 | [Download](https://huggingface.co/CyberHarem/frost_arknights/resolve/main/1530/frost_arknights.zip) | ![pattern_0](1530/previews/pattern_0.png) | ![portrait_0](1530/previews/portrait_0.png) | ![portrait_1](1530/previews/portrait_1.png) | ![portrait_2](1530/previews/portrait_2.png) | ![full_body_0](1530/previews/full_body_0.png) | ![full_body_1](1530/previews/full_body_1.png) | ![profile_0](1530/previews/profile_0.png) | ![profile_1](1530/previews/profile_1.png) | ![free_0](1530/previews/free_0.png) | ![free_1](1530/previews/free_1.png) | ![shorts](1530/previews/shorts.png) | ![maid_0](1530/previews/maid_0.png) | ![maid_1](1530/previews/maid_1.png) | ![miko](1530/previews/miko.png) | ![yukata](1530/previews/yukata.png) | ![suit](1530/previews/suit.png) | ![china](1530/previews/china.png) | ![bikini_0](1530/previews/bikini_0.png) | ![bikini_1](1530/previews/bikini_1.png) | ![bikini_2](1530/previews/bikini_2.png) | ![sit](1530/previews/sit.png) | ![squat](1530/previews/squat.png) | ![kneel](1530/previews/kneel.png) | ![jump](1530/previews/jump.png) | ![crossed_arms](1530/previews/crossed_arms.png) | ![angry](1530/previews/angry.png) | ![smile](1530/previews/smile.png) | ![cry](1530/previews/cry.png) | ![grin](1530/previews/grin.png) | ![n_lie_0](1530/previews/n_lie_0.png) | ![n_lie_1](1530/previews/n_lie_1.png) | ![n_stand_0](1530/previews/n_stand_0.png) | ![n_stand_1](1530/previews/n_stand_1.png) | ![n_stand_2](1530/previews/n_stand_2.png) | ![n_sex_0](1530/previews/n_sex_0.png) | ![n_sex_1](1530/previews/n_sex_1.png) |
| 1800 | 60 | 0.242 | 0.966 | 0.841 | 0.854 | [Download](https://huggingface.co/CyberHarem/frost_arknights/resolve/main/1800/frost_arknights.zip) | ![pattern_0](1800/previews/pattern_0.png) | ![portrait_0](1800/previews/portrait_0.png) | ![portrait_1](1800/previews/portrait_1.png) | ![portrait_2](1800/previews/portrait_2.png) | ![full_body_0](1800/previews/full_body_0.png) | ![full_body_1](1800/previews/full_body_1.png) | ![profile_0](1800/previews/profile_0.png) | ![profile_1](1800/previews/profile_1.png) | ![free_0](1800/previews/free_0.png) | ![free_1](1800/previews/free_1.png) | ![shorts](1800/previews/shorts.png) | ![maid_0](1800/previews/maid_0.png) | ![maid_1](1800/previews/maid_1.png) | ![miko](1800/previews/miko.png) | ![yukata](1800/previews/yukata.png) | ![suit](1800/previews/suit.png) | ![china](1800/previews/china.png) | ![bikini_0](1800/previews/bikini_0.png) | ![bikini_1](1800/previews/bikini_1.png) | ![bikini_2](1800/previews/bikini_2.png) | ![sit](1800/previews/sit.png) | ![squat](1800/previews/squat.png) | ![kneel](1800/previews/kneel.png) | ![jump](1800/previews/jump.png) | ![crossed_arms](1800/previews/crossed_arms.png) | ![angry](1800/previews/angry.png) | ![smile](1800/previews/smile.png) | ![cry](1800/previews/cry.png) | ![grin](1800/previews/grin.png) | ![n_lie_0](1800/previews/n_lie_0.png) | ![n_lie_1](1800/previews/n_lie_1.png) | ![n_stand_0](1800/previews/n_stand_0.png) | ![n_stand_1](1800/previews/n_stand_1.png) | ![n_stand_2](1800/previews/n_stand_2.png) | ![n_sex_0](1800/previews/n_sex_0.png) | ![n_sex_1](1800/previews/n_sex_1.png) |
| 2250 | 75 | 0.206 | **0.977** | 0.842 | 0.759 | [Download](https://huggingface.co/CyberHarem/frost_arknights/resolve/main/2250/frost_arknights.zip) | ![pattern_0](2250/previews/pattern_0.png) | ![portrait_0](2250/previews/portrait_0.png) | ![portrait_1](2250/previews/portrait_1.png) | ![portrait_2](2250/previews/portrait_2.png) | ![full_body_0](2250/previews/full_body_0.png) | ![full_body_1](2250/previews/full_body_1.png) | ![profile_0](2250/previews/profile_0.png) | ![profile_1](2250/previews/profile_1.png) | ![free_0](2250/previews/free_0.png) | ![free_1](2250/previews/free_1.png) | ![shorts](2250/previews/shorts.png) | ![maid_0](2250/previews/maid_0.png) | ![maid_1](2250/previews/maid_1.png) | ![miko](2250/previews/miko.png) | ![yukata](2250/previews/yukata.png) | ![suit](2250/previews/suit.png) | ![china](2250/previews/china.png) | ![bikini_0](2250/previews/bikini_0.png) | ![bikini_1](2250/previews/bikini_1.png) | ![bikini_2](2250/previews/bikini_2.png) | ![sit](2250/previews/sit.png) | ![squat](2250/previews/squat.png) | ![kneel](2250/previews/kneel.png) | ![jump](2250/previews/jump.png) | ![crossed_arms](2250/previews/crossed_arms.png) | ![angry](2250/previews/angry.png) | ![smile](2250/previews/smile.png) | ![cry](2250/previews/cry.png) | ![grin](2250/previews/grin.png) | ![n_lie_0](2250/previews/n_lie_0.png) | ![n_lie_1](2250/previews/n_lie_1.png) | ![n_stand_0](2250/previews/n_stand_0.png) | ![n_stand_1](2250/previews/n_stand_1.png) | ![n_stand_2](2250/previews/n_stand_2.png) | ![n_sex_0](2250/previews/n_sex_0.png) | ![n_sex_1](2250/previews/n_sex_1.png) |
| 1710 | 57 | 0.204 | 0.977 | 0.845 | 0.758 | [Download](https://huggingface.co/CyberHarem/frost_arknights/resolve/main/1710/frost_arknights.zip) | ![pattern_0](1710/previews/pattern_0.png) | ![portrait_0](1710/previews/portrait_0.png) | ![portrait_1](1710/previews/portrait_1.png) | ![portrait_2](1710/previews/portrait_2.png) | ![full_body_0](1710/previews/full_body_0.png) | ![full_body_1](1710/previews/full_body_1.png) | ![profile_0](1710/previews/profile_0.png) | ![profile_1](1710/previews/profile_1.png) | ![free_0](1710/previews/free_0.png) | ![free_1](1710/previews/free_1.png) | ![shorts](1710/previews/shorts.png) | ![maid_0](1710/previews/maid_0.png) | ![maid_1](1710/previews/maid_1.png) | ![miko](1710/previews/miko.png) | ![yukata](1710/previews/yukata.png) | ![suit](1710/previews/suit.png) | ![china](1710/previews/china.png) | ![bikini_0](1710/previews/bikini_0.png) | ![bikini_1](1710/previews/bikini_1.png) | ![bikini_2](1710/previews/bikini_2.png) | ![sit](1710/previews/sit.png) | ![squat](1710/previews/squat.png) | ![kneel](1710/previews/kneel.png) | ![jump](1710/previews/jump.png) | ![crossed_arms](1710/previews/crossed_arms.png) | ![angry](1710/previews/angry.png) | ![smile](1710/previews/smile.png) | ![cry](1710/previews/cry.png) | ![grin](1710/previews/grin.png) | ![n_lie_0](1710/previews/n_lie_0.png) | ![n_lie_1](1710/previews/n_lie_1.png) | ![n_stand_0](1710/previews/n_stand_0.png) | ![n_stand_1](1710/previews/n_stand_1.png) | ![n_stand_2](1710/previews/n_stand_2.png) | ![n_sex_0](1710/previews/n_sex_0.png) | ![n_sex_1](1710/previews/n_sex_1.png) |
## Anything Else?
Because the automation of LoRA training always annoys some people. So for the following groups, it is not recommended to use this model and we express regret:
1. Individuals who cannot tolerate any deviations from the original character design, even in the slightest detail.
2. Individuals who are facing the application scenarios with high demands for accuracy in recreating character outfits.
3. Individuals who cannot accept the potential randomness in AI-generated images based on the Stable Diffusion algorithm.
4. Individuals who are not comfortable with the fully automated process of training character models using LoRA, or those who believe that training character models must be done purely through manual operations to avoid disrespecting the characters.
5. Individuals who finds the generated image content offensive to their values.
## All Steps
We uploaded the files in all steps. you can check the images, metrics and download them in the following links:
* [Steps From 1620 to 2400](all/0.md)
* [Steps From 720 to 1530](all/1.md)
* [Steps From 90 to 630](all/2.md)
|
Yazanveryreal/BOYFRIENDFUNKIN | Yazanveryreal | "2024-02-03T03:55:04Z" | 0 | 0 | null | [
"license:openrail",
"region:us"
] | null | "2024-02-03T03:49:31Z" | ---
license: openrail
---
|
sumanmihir/mimiimi | sumanmihir | "2024-02-03T03:51:46Z" | 0 | 0 | null | [
"license:zlib",
"region:us"
] | null | "2024-02-03T03:51:45Z" | ---
license: zlib
---
|
weimenglin/phi-2-GGUF | weimenglin | "2024-02-03T03:55:05Z" | 0 | 0 | null | [
"gguf",
"endpoints_compatible",
"region:us"
] | null | "2024-02-03T03:53:59Z" | Entry not found |
Sailor01/phi-2-GGUF | Sailor01 | "2024-02-03T03:55:31Z" | 0 | 0 | null | [
"gguf",
"endpoints_compatible",
"region:us"
] | null | "2024-02-03T03:54:21Z" | Entry not found |
dictatee/phi-2-GGUF | dictatee | "2024-02-03T03:55:33Z" | 0 | 0 | null | [
"gguf",
"endpoints_compatible",
"region:us"
] | null | "2024-02-03T03:54:24Z" | Entry not found |
jbuch808/tqc-PandaPickAndPlace-v3 | jbuch808 | "2024-02-03T03:55:57Z" | 0 | 0 | stable-baselines3 | [
"stable-baselines3",
"PandaPickAndPlace-v3",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | reinforcement-learning | "2024-02-03T03:54:51Z" | ---
library_name: stable-baselines3
tags:
- PandaPickAndPlace-v3
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: TQC
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: PandaPickAndPlace-v3
type: PandaPickAndPlace-v3
metrics:
- type: mean_reward
value: -50.00 +/- 0.00
name: mean_reward
verified: false
---
# **TQC** Agent playing **PandaPickAndPlace-v3**
This is a trained model of a **TQC** agent playing **PandaPickAndPlace-v3**
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
...
```
|
Askahoward/phi-2-GGUF | Askahoward | "2024-02-03T03:56:48Z" | 0 | 0 | null | [
"gguf",
"endpoints_compatible",
"region:us"
] | null | "2024-02-03T03:55:50Z" | Entry not found |
ackerley/phi-2-GGUF | ackerley | "2024-02-03T03:58:05Z" | 0 | 0 | null | [
"gguf",
"endpoints_compatible",
"region:us"
] | null | "2024-02-03T03:56:23Z" | Entry not found |
Deepakkori45/LLAma_classes | Deepakkori45 | "2024-02-03T03:56:49Z" | 0 | 0 | transformers | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | "2024-02-03T03:56:41Z" | ---
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]
|
shuaigetw/phi-2-GGUF | shuaigetw | "2024-02-03T04:14:13Z" | 0 | 0 | null | [
"gguf",
"endpoints_compatible",
"region:us"
] | null | "2024-02-03T03:59:18Z" | Entry not found |
ai-tools-searchs/g | ai-tools-searchs | "2024-07-24T03:46:47Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-02-03T04:00:16Z" | Entry not found |
AdAstra1/q-Taxi-v1 | AdAstra1 | "2024-02-03T04:01:29Z" | 0 | 0 | null | [
"Taxi-v3",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
] | reinforcement-learning | "2024-02-03T04:01:26Z" | ---
tags:
- Taxi-v3
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: q-Taxi-v1
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Taxi-v3
type: Taxi-v3
metrics:
- type: mean_reward
value: 7.56 +/- 2.71
name: mean_reward
verified: false
---
# **Q-Learning** Agent playing1 **Taxi-v3**
This is a trained model of a **Q-Learning** agent playing **Taxi-v3** .
## Usage
```python
model = load_from_hub(repo_id="AdAstra1/q-Taxi-v1", filename="q-learning.pkl")
# Don't forget to check if you need to add additional attributes (is_slippery=False etc)
env = gym.make(model["env_id"])
```
|
InfinityLai/phi-2-GGUF | InfinityLai | "2024-02-03T04:04:17Z" | 0 | 0 | null | [
"gguf",
"endpoints_compatible",
"region:us"
] | null | "2024-02-03T04:03:03Z" | Entry not found |
SakuraLLM/Sakura-14B-Orion-v0.9-Base | SakuraLLM | "2024-03-05T12:53:34Z" | 0 | 0 | null | [
"license:cc-by-nc-sa-4.0",
"region:us"
] | null | "2024-02-03T04:10:54Z" | ---
license: cc-by-nc-sa-4.0
---
|
cognitivecomputations/deepseek-coder-7b-base-v1.5-gguf | cognitivecomputations | "2024-02-03T04:17:04Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-02-03T04:17:04Z" | Entry not found |
frankc350/phi-2-GGUF | frankc350 | "2024-02-03T04:25:32Z" | 0 | 0 | null | [
"gguf",
"endpoints_compatible",
"region:us"
] | null | "2024-02-03T04:23:38Z" | Entry not found |
apejmanefard/BabaEnd | apejmanefard | "2024-02-03T04:57:08Z" | 0 | 0 | null | [
"license:openrail",
"region:us"
] | null | "2024-02-03T04:25:50Z" | ---
license: openrail
---
|
joeldabest638/BorisDaddy-AOK | joeldabest638 | "2024-02-03T04:32:34Z" | 0 | 0 | null | [
"license:openrail",
"region:us"
] | null | "2024-02-03T04:32:09Z" | ---
license: openrail
---
|
pakita/Willam | pakita | "2024-02-03T04:36:27Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-02-03T04:32:53Z" | Entry not found |
Fermat111/FOLARIS | Fermat111 | "2024-02-03T04:47:40Z" | 0 | 0 | peft | [
"peft",
"arxiv:1910.09700",
"base_model:meta-llama/Llama-2-7b-hf",
"base_model:adapter:meta-llama/Llama-2-7b-hf",
"region:us"
] | null | "2024-02-03T04:38:38Z" | ---
library_name: peft
base_model: meta-llama/Llama-2-7b-hf
---
# 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]
- **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 Data 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 Data 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]
## Training procedure
### Framework versions
- PEFT 0.7.0.dev0
## Training procedure
### Framework versions
- PEFT 0.7.0.dev0
|
fedoze/11 | fedoze | "2024-02-03T04:43:12Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-02-03T04:43:10Z" | Entry not found |
InfinityLai/TinyLlama-1.1B-Chat-v0.1-AWQ | InfinityLai | "2024-02-03T04:44:47Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-02-03T04:44:47Z" | Entry not found |
ltse5/gwclunarlander | ltse5 | "2024-02-10T15:35:11Z" | 0 | 0 | stable-baselines3 | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | reinforcement-learning | "2024-02-03T04:48:30Z" | ---
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: -139.07 +/- 45.01
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
...
```
|
aboutmattlaw/home | aboutmattlaw | "2024-02-03T04:48:41Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-02-03T04:48:40Z" | Entry not found |
LuccS2/LucaoT | LuccS2 | "2024-02-03T04:52:17Z" | 0 | 0 | null | [
"license:openrail",
"region:us"
] | null | "2024-02-03T04:49:02Z" | ---
license: openrail
---
|
tiennv/pretrain-condetr-pc2-ckpt70k | tiennv | "2024-02-03T04:53:33Z" | 0 | 0 | transformers | [
"transformers",
"pytorch",
"conditional_detr",
"object-detection",
"endpoints_compatible",
"region:us"
] | object-detection | "2024-02-03T04:52:41Z" | Entry not found |