url
stringlengths 23
7.17k
| text
stringlengths 0
1.65M
|
---|---|
https://huggingface.co/v-moayman | Mohamed Ayman
v-moayman
Research interests
None yet
Organizations
models
None public yet
datasets
None public yet |
https://huggingface.co/ranka47 | Sumeet
ranka47
rank47
Research interests
None yet
Organizations
models
None public yet
datasets
None public yet |
https://huggingface.co/Abduali | 1 5
Abdur Raheem Ali
Abduali
abduali
Research interests
None yet
Organizations
models
None public yet
datasets
None public yet |
https://huggingface.co/wzhings | 1
Zuhui Wang
wzhings
Research interests
None yet
Organizations
models
None public yet
datasets
None public yet |
https://huggingface.co/Alexhughes132 | Alexander Hughes
Alexhughes132
Research interests
Machine learning, green computing, social computing
Organizations |
https://huggingface.co/unilm | 12 12 5
UniLM
unilm
Research interests
Language Model Pre-Training
Organizations
Papers 3
arxiv:2106.08254
arxiv:2306.07174
arxiv:2306.14824
spaces 1
3
🌍
Promptist
models
None public yet
datasets
None public yet |
https://huggingface.co/yizhezhang | Yizhe Zhang
yizhezhang
http://yizhezhang.net
dreasysnail
Research interests
Natural language generation
Organizations
Papers 1
arxiv:2306.05544
models
None public yet
datasets
None public yet |
https://huggingface.co/liminghao1630 | 1
Minghao Li
liminghao1630
liminghao1630
Research interests
None yet
Organizations
spaces 1
Runtime error
6
🦀
TrOCR Printed
models
None public yet
datasets
None public yet |
https://huggingface.co/tnaumann | 1
Tristan Naumann
tnaumann
TristanNaumann
tnaumann
Research interests
None yet
Organizations
Papers 10
arxiv:2007.15779
arxiv:1904.03323
arxiv:2204.09817
arxiv:2112.07869
models
None public yet
datasets
None public yet |
https://huggingface.co/xutan | 4
Xu Tan
xutan
tobyoup
Research interests
None yet
Organizations
Papers 11
arxiv:1905.09263
arxiv:2303.17580
arxiv:2305.10841
arxiv:2305.19835
models
None public yet
datasets
None public yet |
https://huggingface.co/naotous | Naoto Usuyama
naotous
Research interests
Machine Reading for Precision Medicine
Organizations
Papers 6 |
https://huggingface.co/codebert | 4 5
CodeBERT
codebert
guoday
Research interests
None yet
Organizations
models
None public yet
datasets
None public yet |
https://huggingface.co/DeBERTa | 5
Pengcheng He
DeBERTa
https://github.com/microsoft/DeBERTa
BigBird01
Research interests
None yet
Organizations
Papers 2
arxiv:2305.02483
arxiv:2309.03883
models 1
DeBERTa/deberta-v2-xxlarge
Updated Feb 11, 2021
datasets
None public yet |
https://huggingface.co/KaitaoSong | Kaitao Song
KaitaoSong
StillKeepTry
Research interests
None yet
Organizations
Papers 4
arxiv:2303.17580
arxiv:2305.19835
arxiv:2309.02285
arxiv:2309.08532
models 1
KaitaoSong/MPNet
Updated 20 days ago • 1
datasets
None public yet |
https://huggingface.co/SivilTaram | Qian Liu
SivilTaram
Research interests
Semantic parsing
Organizations
Papers 4
models 13
SivilTaram/tapex-t5-large-finetuned-wtq
Text2Text Generation • Updated Jun 30, 2022
SivilTaram/tapex-t5-xl-finetuned-wtq
Text2Text Generation • Updated Jun 30, 2022
SivilTaram/tapex-t5-small-lm-adapt
Text2Text Generation • Updated Jun 30, 2022
SivilTaram/tapex-t5-large-lm-adapt
Text2Text Generation • Updated Jun 30, 2022
SivilTaram/tapex-t5-xl-lm-adapt
Text2Text Generation • Updated Jun 30, 2022
SivilTaram/tapex-t5-base-lm-adapt
Updated Jun 30, 2022
SivilTaram/poet-sql-finetuned-hotpotqa
Updated Jun 30, 2022
SivilTaram/poet-sql-roberta
Updated Jun 30, 2022
SivilTaram/poet-sql-digit-finetuned-drop
Updated Jun 29, 2022
SivilTaram/poet-math-digit
Updated Jun 29, 2022
datasets 1 |
https://huggingface.co/xiongchenyan | 1 2
Chenyan Xiong
xiongchenyan
https://www.microsoft.com/en-us/research/people/cxiong/
xiongchenyan
Research interests
None yet
Organizations
Papers 1
arxiv:1904.07531
models
None public yet
datasets
None public yet |
https://huggingface.co/roberttinn | 1
robert tinn
roberttinn
r-tinn
Research interests
None yet
Organizations
models
None public yet
datasets
None public yet |
https://huggingface.co/ranpox | 11 12 1
Yiheng Xu
ranpox
https://yihengxu.com/
ranpox
Research interests
None yet
Organizations
models
None public yet
datasets 1
ranpox/xfund
Viewer • Updated Sep 8, 2021 • 175 • 3 |
https://huggingface.co/harish586 | 2
harish yenala
harish586
Research interests
Deep learning, Natural language processing
Organizations
models
None public yet
datasets
None public yet |
https://huggingface.co/sourabhxiii | Sourabh Maity
sourabhxiii
sourabhxiii
Research interests
None yet
Organizations
models
None public yet
datasets
None public yet |
https://huggingface.co/jw2yang | Jianwei Yang
jw2yang
Research interests
Computer Vision, Vision and Language, Machine Learning
Organizations
Papers 3
spaces 2 |
https://huggingface.co/santiagxf | Facundo Santiago
santiagxf
https://medium.com/@santiagof
santiagxf
Research interests
None yet
Organizations
models
None public yet
datasets 1
santiagxf/spanish-marketing-tweets
Viewer • Updated Jul 3, 2022 |
https://huggingface.co/Lusen | Dong
Lusen
cicolord
Research interests
None yet
Organizations
models
None public yet
datasets
None public yet |
https://huggingface.co/subho | Subhabrata Mukherjee
subho
https://www.microsoft.com/en-us/research/people/submukhe/
subho_mpi
subhomj
Research interests
NLP, DL
Organizations
Papers 2
arxiv:2306.02707
arxiv:2307.02628
models
None public yet
datasets
None public yet |
https://huggingface.co/gkcalat | Ablai
gkcalat
gkcalat
Research interests
None yet
Organizations
models
None public yet
datasets
None public yet |
https://huggingface.co/manojsb | 2
Manoj Bableshwar
manojsb
Research interests
None yet
Organizations
models
None public yet
datasets
None public yet |
https://huggingface.co/estyle | 8
Tengchao Lv
estyle
Dod-o
Research interests
None yet
Organizations
Papers 3
arxiv:2203.02378
arxiv:2204.08387
arxiv:2309.11419
models
None public yet
datasets
None public yet |
https://huggingface.co/tellarin | Börje Karlsson
tellarin
Research interests
Machine Learning Systems, Mobile Sensing, Knowledge Mining, Digital Entertainment
Organizations
Papers 3 |
https://huggingface.co/christoph-stuber | Christoph Stuber
christoph-stuber
Research interests
None yet
Organizations
models
None public yet
datasets
None public yet |
https://huggingface.co/eddie-cheung | Eddie Cheung
eddie-cheung
Research interests
None yet
Organizations
models
None public yet
datasets
None public yet |
https://huggingface.co/grammarly/coedit-large | Model Card for CoEdIT-Large
This model was obtained by fine-tuning the corresponding google/flan-t5-large model on the CoEdIT dataset. Details of the dataset can be found in our paper and repository.
Paper: CoEdIT: Text Editing by Task-Specific Instruction Tuning
Authors: Vipul Raheja, Dhruv Kumar, Ryan Koo, Dongyeop Kang
Model Details
Model Description
Language(s) (NLP): English
Finetuned from model: google/flan-t5-large
Model Sources
Repository: https://github.com/vipulraheja/coedit
Paper: https://arxiv.org/abs/2305.09857
How to use
We make available the models presented in our paper.
Model Number of parameters
CoEdIT-large 770M
CoEdIT-xl 3B
CoEdIT-xxl 11B
Uses
Text Revision Task
Given an edit instruction and an original text, our model can generate the edited version of the text.
Usage
from transformers import AutoTokenizer, T5ForConditionalGeneration tokenizer = AutoTokenizer.from_pretrained("grammarly/coedit-large") model = T5ForConditionalGeneration.from_pretrained("grammarly/coedit-large") input_text = 'Fix grammatical errors in this sentence: When I grow up, I start to understand what he said is quite right.' input_ids = tokenizer(input_text, return_tensors="pt").input_ids outputs = model.generate(input_ids, max_length=256) edited_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
Software
https://github.com/vipulraheja/coedit
Citation
BibTeX:
@article{raheja2023coedit, title={CoEdIT: Text Editing by Task-Specific Instruction Tuning}, author={Vipul Raheja and Dhruv Kumar and Ryan Koo and Dongyeop Kang}, year={2023}, eprint={2305.09857}, archivePrefix={arXiv}, primaryClass={cs.CL} }
APA: Raheja, V., Kumar, D., Koo, R., & Kang, D. (2023). CoEdIT: Text Editing by Task-Specific Instruction Tuning. ArXiv. /abs/2305.09857 |
https://huggingface.co/couturierc | Camille Couturier
couturierc
Research interests
Efficient inference, Generalization across domains
Organizations |
https://huggingface.co/nielsr | Niels Rogge
nielsr
Research interests
Mainly interested in diving into complex Github repos and making AI easier and more accessible to everyone
Organizations
Collections 1
spaces 19
models 135
datasets 72 |
https://huggingface.co/grammarly/coedit-xxl | Model Card for CoEdIT-xxl
This model was obtained by fine-tuning the corresponding google/flan-t5-xxl model on the CoEdIT dataset.
Paper: CoEdIT: ext Editing by Task-Specific Instruction Tuning
Authors: Vipul Raheja, Dhruv Kumar, Ryan Koo, Dongyeop Kang
Model Details
Model Description
Language(s) (NLP): English
Finetuned from model: google/flan-t5-xxl
Model Sources
Repository: https://github.com/vipulraheja/coedit
Paper: https://arxiv.org/abs/2305.09857
How to use
We make available the models presented in our paper.
Model Number of parameters
CoEdIT-large 770M
CoEdIT-xl 3B
CoEdIT-xxl 11B
Uses
Text Revision Task
Given an edit instruction and an original text, our model can generate the edited version of the text.
Usage
from transformers import AutoTokenizer, T5ForConditionalGeneration tokenizer = AutoTokenizer.from_pretrained("grammarly/coedit-xxl") model = T5ForConditionalGeneration.from_pretrained("grammarly/coedit-xxl") input_text = 'Fix grammatical errors in this sentence: When I grow up, I start to understand what he said is quite right.' input_ids = tokenizer(input_text, return_tensors="pt").input_ids outputs = model.generate(input_ids, max_length=256) edited_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
Software
https://github.com/vipulraheja/coedit
Citation
BibTeX:
@article{raheja2023coedit, title={CoEdIT: Text Editing by Task-Specific Instruction Tuning}, author={Vipul Raheja and Dhruv Kumar and Ryan Koo and Dongyeop Kang}, year={2023}, eprint={2305.09857}, archivePrefix={arXiv}, primaryClass={cs.CL} }
APA: Raheja, V., Kumar, D., Koo, R., & Kang, D. (2023). CoEdIT: Text Editing by Task-Specific Instruction Tuning. ArXiv. /abs/2305.09857 |
https://huggingface.co/grammarly/detexd-roberta-base | DeTexD-RoBERTa-base delicate text detection
This is a baseline RoBERTa-base model for the delicate text detection task.
Paper: DeTexD: A Benchmark Dataset for Delicate Text Detection
GitHub repository
The labels meaning according to the paper:
LABEL_0 -> non-delicate (0)
LABEL_1 -> very low risk (1)
LABEL_2 -> low risk (2)
LABEL_3 -> medium risk (3)
LABEL_4 -> high risk (4)
LABEL_5 -> very high risk (5)
Classification example code
Here's a short usage example with the torch library in a binary classification task:
from transformers import pipeline classifier = pipeline("text-classification", model="grammarly/detexd-roberta-base") def predict_binary_score(text: str): # get multiclass probability scores scores = classifier(text, top_k=None) # convert to a single score by summing the probability scores # for the higher-index classes return sum(score['score'] for score in scores if score['label'] in ('LABEL_3', 'LABEL_4', 'LABEL_5')) def predict_delicate(text: str, threshold=0.72496545): return predict_binary_score(text) > threshold print(predict_delicate("Time flies like an arrow. Fruit flies like a banana."))
Expected output:
False
Citation Information
@inproceedings{chernodub-etal-2023-detexd, title = "{D}e{T}ex{D}: A Benchmark Dataset for Delicate Text Detection", author = "Yavnyi, Serhii and Sliusarenko, Oleksii and Razzaghi, Jade and Mo, Yichen and Hovakimyan, Knar and Chernodub, Artem", booktitle = "The 7th Workshop on Online Abuse and Harms (WOAH)", month = jul, year = "2023", address = "Toronto, Canada", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/2023.woah-1.2", pages = "14--28", abstract = "Over the past few years, much research has been conducted to identify and regulate toxic language. However, few studies have addressed a broader range of sensitive texts that are not necessarily overtly toxic. In this paper, we introduce and define a new category of sensitive text called {``}delicate text.{''} We provide the taxonomy of delicate text and present a detailed annotation scheme. We annotate DeTexD, the first benchmark dataset for delicate text detection. The significance of the difference in the definitions is highlighted by the relative performance deltas between models trained each definitions and corpora and evaluated on the other. We make publicly available the DeTexD Benchmark dataset, annotation guidelines, and baseline model for delicate text detection.", } |
https://huggingface.co/grammarly/pseudonymization-seq2seq | Model Card for Model ID
This repository contains files for two Seq2Seq transformers-based models used in our paper: https://aclanthology.org/2023.trustnlp-1.20/.
Model Details
Model Description
Developed by: Oleksandr Yermilov, Vipul Raheja, Artem Chernodub
Model type: Seq2Seq
Language (NLP): English
License: Apache license 2.0
Finetuned from model: BART
Model Sources
Paper: https://aclanthology.org/2023.trustnlp-1.20/
Uses
These models can be used for anonymizing datasets in English language.
Bias, Risks, and Limitations
Please check the Limitations section in our paper.
Training Details
Training Data
https://huggingface.co/datasets/grammarly/pseudonymization-data/tree/main/seq2seq
Training Procedure
Gather text data from Wikipedia.
Preprocess it using NER-based pseudonymization.
Fine-tune BART model on translation task for translating text from "original" to "pseudonymized".
Training Hyperparameters
We train the models for 3 epochs using AdamW optimization with the learning rate α =2*105, and the batch size is 8.
Evaluation
Factors & Metrics
Factors
There is no source truth of named entities for the data, on which this model was trained. We check whether the word is a named entity, using one of the NER systems (spaCy or FLAIR).
Metrics
We measure the amount of text, changed by our model. Specifically, we check for the following categories of translated text word by word:
True positive (TP) - Named entity, which was changed to another named entity.
True negative (TN) - Not a named entity, which was not changed.
False positive (FP) - Not a named entity, which was changed to another word.
False negative (FN) - Named entity, which was not changed to another named entity. We calculate F1 score based on the abovementioned values.
Citation
BibTeX:
@inproceedings{yermilov-etal-2023-privacy, title = "Privacy- and Utility-Preserving {NLP} with Anonymized data: A case study of Pseudonymization", author = "Yermilov, Oleksandr and Raheja, Vipul and Chernodub, Artem", booktitle = "Proceedings of the 3rd Workshop on Trustworthy Natural Language Processing (TrustNLP 2023)", month = jul, year = "2023", address = "Toronto, Canada", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/2023.trustnlp-1.20", doi = "10.18653/v1/2023.trustnlp-1.20", pages = "232--241", abstract = "This work investigates the effectiveness of different pseudonymization techniques, ranging from rule-based substitutions to using pre-trained Large Language Models (LLMs), on a variety of datasets and models used for two widely used NLP tasks: text classification and summarization. Our work provides crucial insights into the gaps between original and anonymized data (focusing on the pseudonymization technique) and model quality and fosters future research into higher-quality anonymization techniques better to balance the trade-offs between data protection and utility preservation. We make our code, pseudonymized datasets, and downstream models publicly available.", }
Model Card Contact
Oleksandr Yermilov (oleksandr.yermilov@ucu.edu.ua). |
https://huggingface.co/grammarly/coedit-xl-composite | Model Card for CoEdIT-xl-composite
This model was obtained by fine-tuning the corresponding google/flan-t5-xl model on the CoEdIT-Composite dataset. Details of the dataset can be found in our paper and repository.
Paper: CoEdIT: Text Editing by Task-Specific Instruction Tuning
Authors: Vipul Raheja, Dhruv Kumar, Ryan Koo, Dongyeop Kang
Model Details
Model Description
Language(s) (NLP): English
Finetuned from model: google/flan-t5-xl
Model Sources
Repository: https://github.com/vipulraheja/coedit
Paper: https://arxiv.org/abs/2305.09857
How to use
We make available the models presented in our paper.
Model Number of parameters
CoEdIT-large 770M
CoEdIT-xl 3B
CoEdIT-xxl 11B
Uses
Text Revision Task
Given an edit instruction and an original text, our model can generate the edited version of the text.
This model can also perform edits on composite instructions, as shown below:
Usage
from transformers import AutoTokenizer, T5ForConditionalGeneration tokenizer = AutoTokenizer.from_pretrained("grammarly/coedit-xl-composite") model = T5ForConditionalGeneration.from_pretrained("grammarly/coedit-xl-composite") input_text = 'Fix grammatical errors in this sentence and make it simpler: When I grow up, I start to understand what he said is quite right.' input_ids = tokenizer(input_text, return_tensors="pt").input_ids outputs = model.generate(input_ids, max_length=256) edited_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
Software
https://github.com/vipulraheja/coedit
Citation
BibTeX:
@article{raheja2023coedit, title={CoEdIT: Text Editing by Task-Specific Instruction Tuning}, author={Vipul Raheja and Dhruv Kumar and Ryan Koo and Dongyeop Kang}, year={2023}, eprint={2305.09857}, archivePrefix={arXiv}, primaryClass={cs.CL} }
APA: Raheja, V., Kumar, D., Koo, R., & Kang, D. (2023). CoEdIT: Text Editing by Task-Specific Instruction Tuning. ArXiv. /abs/2305.09857 |
https://huggingface.co/datasets/grammarly/pseudonymization-data | This repository contains all the datasets used in our paper "Privacy- and Utility-Preserving NLP with Anonymized data: A case study of Pseudonymization" (https://aclanthology.org/2023.trustnlp-1.20).
Dataset Card for Pseudonymization data
Dataset Summary
This dataset repository contains all the datasets, used in our paper. It includes datasets for different NLP tasks, pseudonymized by different algorithms; a dataset for training Seq2Seq model which translates text from original to "pseudonymized"; and a dataset for training model which would detect if the text was pseudonymized.
Languages
English.
Dataset Structure
Each folder contains preprocessed train versions of different datasets (e.g, in the cnn_dm folder there will be preprocessed CNN/Daily Mail dataset). Each file has a name, which corresponds with the algorithm from the paper used for its preprocessing (e.g. ner_ps_spacy_imdb.csv is imdb dataset, preprocessed with NER-based pseudonymization using FLAIR system). I
Dataset Creation
Datasets in imdb and cnn_dm folders were created by pseudonymizing corresponding datasets with different pseudonymization algorithms.
Datasets in detection folder are combined original datasets and pseudonymized datasets, grouped by pseudonymization algorithm used.
Datasets in seq2seq folder are datasets for training Seq2Seq transformer-based pseudonymization model. At first, a dataset was fetched from Wikipedia articles, which was preprocessed with either NER-PSFLAIR or NER-PSspaCy algorithms.
Personal and Sensitive Information
This datasets bring no sensitive or personal information; it is completely based on data present in open sources (Wikipedia, standard datasets for NLP tasks).
Considerations for Using the Data
Known Limitations
Only English texts are present in the datasets. Only a limited part of named entity types are replaced in the datasets. Please, also check the Limitations section of our paper.
Additional Information
Dataset Curators
Oleksandr Yermilov (oleksandr.yermilov@ucu.edu.ua)
Citation Information
@inproceedings{yermilov-etal-2023-privacy, title = "Privacy- and Utility-Preserving {NLP} with Anonymized data: A case study of Pseudonymization", author = "Yermilov, Oleksandr and Raheja, Vipul and Chernodub, Artem", booktitle = "Proceedings of the 3rd Workshop on Trustworthy Natural Language Processing (TrustNLP 2023)", month = jul, year = "2023", address = "Toronto, Canada", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/2023.trustnlp-1.20", doi = "10.18653/v1/2023.trustnlp-1.20", pages = "232--241", abstract = "This work investigates the effectiveness of different pseudonymization techniques, ranging from rule-based substitutions to using pre-trained Large Language Models (LLMs), on a variety of datasets and models used for two widely used NLP tasks: text classification and summarization. Our work provides crucial insights into the gaps between original and anonymized data (focusing on the pseudonymization technique) and model quality and fosters future research into higher-quality anonymization techniques better to balance the trade-offs between data protection and utility preservation. We make our code, pseudonymized datasets, and downstream models publicly available.", }
Downloads last month9
Models trained or fine-tuned on grammarly/pseudonymization-data |
https://huggingface.co/Viktor | Zamaruiev
Viktor
Research interests
None yet
Organizations
models
None public yet
datasets
None public yet |
https://huggingface.co/grammarly/coedit-xl | Model Card for CoEdIT-xl
This model was obtained by fine-tuning the corresponding google/flan-t5-xl model on the CoEdIT dataset. Details of the dataset can be found in our paper and repository.
Paper: CoEdIT: Text Editing by Task-Specific Instruction Tuning
Authors: Vipul Raheja, Dhruv Kumar, Ryan Koo, Dongyeop Kang
Model Details
Model Description
Language(s) (NLP): English
Finetuned from model: google/flan-t5-xl
Model Sources
Repository: https://github.com/vipulraheja/coedit
Paper: https://arxiv.org/abs/2305.09857
How to use
We make available the models presented in our paper.
Model Number of parameters
CoEdIT-large 770M
CoEdIT-xl 3B
CoEdIT-xxl 11B
Uses
Text Revision Task
Given an edit instruction and an original text, our model can generate the edited version of the text.
Usage
from transformers import AutoTokenizer, T5ForConditionalGeneration tokenizer = AutoTokenizer.from_pretrained("grammarly/coedit-xl") model = T5ForConditionalGeneration.from_pretrained("grammarly/coedit-xl") input_text = 'Fix grammatical errors in this sentence: When I grow up, I start to understand what he said is quite right.' input_ids = tokenizer(input_text, return_tensors="pt").input_ids outputs = model.generate(input_ids, max_length=256) edited_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
Software
https://github.com/vipulraheja/coedit
Citation
BibTeX:
@article{raheja2023coedit, title={CoEdIT: Text Editing by Task-Specific Instruction Tuning}, author={Vipul Raheja and Dhruv Kumar and Ryan Koo and Dongyeop Kang}, year={2023}, eprint={2305.09857}, archivePrefix={arXiv}, primaryClass={cs.CL} }
APA: Raheja, V., Kumar, D., Koo, R., & Kang, D. (2023). CoEdIT: Text Editing by Task-Specific Instruction Tuning. ArXiv. /abs/2305.09857 |
https://huggingface.co/datasets/grammarly/coedit | Remove all grammatical errors from this text: For example, countries with a lot of deserts can terraform their desert to increase their habitable land and using irrigation to provide clean water to the desert.
For example, countries with a lot of deserts can transform their desert to increase their habitable land and use irrigation to provide clean water to the desert.
Improve the grammaticality: As the number of people grows, the need of habitable environment is unquestionably essential.
As the number of people grows, the need for a habitable environment is unquestionably increasing.
Improve the grammaticality of this sentence: Besides some technologically determinists that allow the development of biometric identification, this technology is also shaped by three social factors, namely, the desire of the society for safety, convenience and economy.
Besides some technological determinists that allow the development of biometric identification, this technology is also shaped by three social factors, namely, the desire of society for safety, convenience, and economy.
Remove all grammatical errors from this text: Safety is one of the crucial problems that many countries and companies concern.
Safety is one of the crucial problems that many countries and companies are concerned about.
Fix grammaticality in this sentence: On one hand more and more virus and hack can access personal computers, so the secret data and documents may be stolen.
On the one hand, more and more viruses and hackers can access personal computers, so secret data and documents may be stolen.
Improve the grammar of this text: We can have fingerprint verification reader combined with built-in smartcard reader, and it only takes seconds to verify one's identification.
We can have a fingerprint verification reader combined with a built-in smart card reader, and it only takes seconds to verify one's identification.
Fix grammar in this sentence: Nuclear technology had come a long way since Ernest Rutherford first split the atom in 1917.
Nuclear technology has come a long way since Ernest Rutherford first split the atom in 1917.
Fix grammar in the sentence: The subsequent realization that the additional neutrons produced from fission reaction can induce a nuclear chain reaction sparked off widespread interest in nuclear technology.
The subsequent realization that the additional neutrons produced from a fission reaction could induce a nuclear chain reaction has sparked a widespread interest in nuclear technology.
Update to remove grammar errors: The leakage of radioactive gas into the atmosphere prompted the many anti-nuclear demonstrations that sprung up across the America in the following months.
The leakage of radioactive gas into the atmosphere prompted the many anti-nuclear demonstrations that sprang up across America in the following months.
Fix grammaticality in this sentence: Although the reactor was eventually cleaned up and decontaminated, the damaged dealt to nuclear power was irreversible and caused its subsequent decline.
Although the reactor was eventually cleaned up and decontaminated, the damage dealt to nuclear power was irreversible and caused its subsequent decline.
Improve the grammar of this text: To partly offset this gigantic demand for energy, China had launched an ambitious program to produce 16% of its electricity from nuclear power by 2030.
To partly offset this gigantic demand for energy, China has launched an ambitious program to produce 16% of its electricity from nuclear power by 2030.
Fix grammar errors in this sentence: This endeavor to produce more nuclear power have stimulated the development of safer designs of nuclear reactors.
This endeavor to produce more nuclear power has stimulated the development of safer designs for nuclear reactors.
Improve the grammaticality of this sentence: In conclusion, nuclear technology development had always been driven by social factors.
In conclusion, nuclear technology development has always been driven by social factors.
Improve the grammaticality: World War 2 had given it momentum in its initial research, but it will be mankind's need for a renewable and environmentally friendly energy source that will drive nuclear technology's future developments.
World War 2 has given it momentum in its initial research, but it will be mankind's need for a renewable and environmentally friendly energy source that will drive nuclear technology's future developments.
Remove grammatical mistakes: These solutions may be generated by analyzing existing products to find out how the weaknesses can be improved while retaining the strength.
These solutions may be generated by analyzing existing products to find out how the weaknesses can be overcome while retaining the strengths.
Remove all grammatical errors from this text: Therefore careful analysis of the product has to be made before selecting a solution for testing and implementation.
Therefore careful analysis of a product has to be made before selecting a solution for testing and implementation.
Fix disfluencies in the sentence: An example is water which is a good renewable resource and is plentiful.
An example is water, which is a good renewable resource and is plentiful.
Fix grammaticality: This is because a large body of water is needed to harness the same energy produced by a small amount of fuel.
This is because a large body of water is needed to harness the same amount of energy produced by a small amount of fuel.
Fix grammaticality in this sentence: All the solutions will be thoroughly analysed by the engineers before coming to a conclusion.
All the solutions will be thoroughly analyzed by engineers before coming to a conclusion.
Fix grammaticality of the sentence: As a result, students have no chance to develop their creative thinking and gradually become stereotype.
As a result, students have no chance to develop their creative thinking abilities and gradually become.
Fix grammar in the sentence: However, after one year study, he found history not suitable for himself and became interested in physics and showed great talent.
However, after one year's study, he found history not suitable for him and became interested in physics, and showed great talent.
Fix grammar: Whether China can take this chance to catch up with those well-developed countries or even surpass them depends on China's trail of solving the present problems.
Whether China can take this chance to catch up with those well-developed countries or even surpass them depends on China's solving the present problems.
Improve the grammar of this text: If China can come up with effective policy to change its education system and stimulate innovation, China's pace to flourish may become even faster.
If China can come up with an effective policy to change its education system and stimulate innovation, China's pace to flourish may become even faster.
Make the sentence grammatical: The process of developing a new product based on innovation is not an easy task for the innovators.
The process of developing a new product based on innovation is not an easy task for innovators.
Make the sentence grammatical: By diffusion and adoption of the innovation products by the public or specific users, the innovators have to face the consequences.
Through the distribution and adoption of innovative products by the public or specific users, innovators have to face the consequences.
Improve the grammaticality of this text: These are not the only challenges that the innovators are going to deal with.
These are not the only challenges that innovators are going to deal with.
Fix grammar errors: In order to process from the initial stage of innovation development to the final stage, the most important issue is to have a huge sum of fund for development and commercial purposes.
In order to proceed from the initial stage of innovation development to the final stage, the most important issue is to have a huge sum of funds for development and commercial purposes.
Fix grammatical errors in this sentence: So, the manufacture company, for example, the company that the innovators are working for, is one of the major investors that is providing the fund.
So, the manufacturing company, for example, the company that innovators are working for, is one of the major investors that is providing the fund.
Fix all grammatical errors: For example, if the manufacturing company did not earn profit in the market, then in order to reduce the cost and prevent the loss from getting worse, the manufacturing company has to stop funding the innovators for their prototypes development.
For example, if the manufacturing company does not earn profit in the market, then in order to reduce the cost and prevent the loss from getting worse, the manufacturing company has to stop funding the innovators for the development of their prototypes.
Update to remove grammar errors: Then the innovators have to stop all works for the development.
Then the innovators have to stop all work for the development.
Fix the grammatical mistakes: This shows that the manufacturing companies are trying to reduce the unnecessary burden to maintain the companies' stand.
This shows that manufacturing companies are trying to reduce the unnecessary burden to maintain the companies' stand.
Improve the grammaticality: Therefore, this is one of the major factors that will definitely affect the innovators from developing innovation products.
Therefore, this is one of the major factors that will definitely affect innovators from developing innovative products.
Fix errors in this text: For example, the marketing department thinks that the innovated products are not relevant to what the company is selling.
For example, the marketing department thinks that the new products are not relevant to what the company is selling.
Improve the grammaticality of this sentence: They have to obtain fund from the investors in order to develop their innovation prototypes and require help from the marketing department to have their innovation products for sales in the marketplace.
They have to obtain funds from investors in order to develop their innovation prototypes and require help from the marketing department to have their innovative products for sale in the marketplace.
Make the sentence fluent: Engineering design is defined as a process that brings ideas or theories into physical representations which satisfies human needs.
Engineering design is defined as a process that brings ideas or theories into physical representations which satisfy human needs.
Remove all grammatical errors from this text: Because Engineering designs are always related to real problem, during the five processes, the obstacles they face are more than theories and calculations on paper.
Because engineering designs are always related to real problems, during the five processes, the obstacles they face are more than theories and calculations on paper.
Fix the grammatical mistakes: Political issues usually become realized in the beginning and final steps, especially in the last step.
Political issues usually become relevant in the beginning and final steps, especially in the last step.
Fix grammatical errors: In the last step of design, political issues also disturb the process significantly.
In the last step of design, political issues can also disrupt the process significantly.
Make the sentence fluent: However, when the design had been carried out for a few weeks, it was stopped.
However, after the design had been carried out for a few weeks, it was stopped.
Fix grammaticality in this sentence: In this example, there is nothing wrong with the original design work, but the design still cannot be carried out due to political inconsistent between the city government and higher level authorities.
In this example, there is nothing wrong with the original design work, but the design still cannot be carried out due to political inconsistency between the city government and higher-level authorities.
Fix grammaticality: It affects the analyzing and test step most seriously though it can affect almost every step of design work.
It affects the analyzing and the test step most seriously though it can affect almost every step of design work.
Fix grammatical errors: Besides, the lack of financial support or sudden stop in the financial support may even lead to the incomplete of a project.
Besides, the lack of financial support or sudden stop in the financial support may even lead to the incompletion of a project.
Grammar improvements: Humankind always has needs and demands because people want to lead more comfortable and easier life.
Humankind always has needs and demands because people want to lead a more comfortable and easier life.
Fix the grammatical mistakes: There are various fields which engineering plays an important role in our daily lives, such as entertainment, healthcare, transportation, real estate, and so on.
There are various fields in which engineering plays an important role in our daily lives, such as entertainment, healthcare, transportation, real estate, and so on.
Improve the grammaticality: The cost of raw materials has risen significantly from the year 2003 to year 2009 and it has affected the electronics supply chain.
The cost of raw materials has risen significantly from the year 2003 to the year 2009, and it has affected the electronics supply chain.
Make the sentence grammatical: Hence designs that need large amount of gold may not be feasible.
Hence designs that need a large amount of gold may not be feasible.
Fix the grammatical mistakes: However, if the engineers were to stick to their original design, the cost of the end product will be high.
However, if the engineers are to stick to their original design, the cost of the end product will be high.
Update to remove grammar errors: Hazardous product can tarnish the reputation of the company and sometimes even result in the loss of innocent lives.
Hazardous products can tarnish the reputation of the company and sometimes even result in the loss of innocent lives.
Fix disfluencies in the sentence: Thus it is very important for engineers to do repeated trial test of the product to ensure that it is free of faults.
Thus it is very important for engineers to do repeated trial tests of the product to ensure that it is free of faults.
Fix grammatical errors: As we understand the relevance and importance of engineering design, we will come to realize that in reality there are several factors that preventing the progress of engineering design.
As we understand the relevance and importance of engineering design, we will come to realize that, in reality, there are several factors that prevent the progress of engineering design.
Fix grammatical mistakes in this sentence: In Singapore, there is only a certain fixed amount in the country's national budget allocated of the research and development sector.
In Singapore, there is a certain fixed amount in the country's national budget allocated to the research and development sector.
Remove grammatical mistakes: Some feel that in these tough economical times, it is wiser to splurge the money on restructuring the economy or providing more incentives to instill entrepreneurship, rather than investing in research in engineering design.
Some feel that in these tough economic times, it is wiser to spend the money on restructuring the economy or providing more incentives to encourage entrepreneurship rather than investing in research in engineering design.
Fix grammaticality of the sentence: Secondly, the amount of creative people in Singapore is small, which may be a major reason for the hampering of innovative engineering design.
Secondly, the number of creative people in Singapore is small, which may be a major reason for the hampering of innovative engineering design.
Fix grammatical errors: The population of Singapore is scarce compared to other countries in the region.
The population of Singapore is small compared to other countries in the region.
Grammar improvements: The impact on having a limited amount of creative people has resulted in Singapore having to resort to buying foreign-based engineering design equipment from overseas.
The impact of having a limited number of creative people has resulted in Singapore having to resort to buying foreign-based engineering design equipment from overseas.
Improve the grammar of this text: However, the 3 M researchers found out this failed bonding agent was suitable for attaching notes which satisfy many people's needs.
However, the 3 M researchers found that this failed bonding agent was suitable for attaching notes which satisfied many people's needs.
Fix grammar in the sentence: Thus post-it note was invented from this idea.
Thus the post-it note was invented from this idea.
Make the sentence fluent: In this manner, many other serendipitous technologies have been discovered and solved many irrelevant problems.
In this manner, many other serendipitous technologies have been discovered and have solved many problems.
Remove grammar mistakes: Thus, it is fair to say that either conventional technology or serendipitous technology is stimulated by the realization of problems and needs.
Thus, it is fair to say that both conventional technology and serendipitous technology are stimulated by the realization of problems and needs.
Fix grammaticality in this sentence: If the refrigerator was remained as it was invented in 1910s and no further development has been made to improve its quality, the refrigerator would just be an unsuccessful invention due to its low efficiency and high cost.
If the refrigerator had remained as it was invented in the 1910s and no further development had been made to improve its quality, the refrigerator would just be an unsuccessful invention due to its low efficiency and high cost.
Fix grammar in the sentence: How other people get to know your products and been convinced to use them.
How other people get to know about your products and are convinced to use them.
Remove grammar mistakes: From these two examples above, it is clear that another similarity between conventional technology and serendipitous technology is the process of development and commercialization which involved a lot of hard work.
From these two examples, it is clear that another similarity between conventional technology and serendipitous technology is the process of development and commercialization which involve a lot of hard work.
Fix disfluencies in the sentence: Research is usually based on certain organizations and it requires some time, funds and resources before the researchers can finally obtain the expected results.
Research is usually based in certain organizations, and it requires some time, funds, and resources before the researchers can finally obtain the expected results.
Fix all grammatical errors: This is, in fact, not encouraged by the traditional idea of Chinese people.
This is, in fact, not encouraged by the traditional philosophy of Chinese people.
Fix grammaticality in this sentence: I believe these problems obstructing engineering innovation will be solved in the near future.
Thus, I believe these problems obstructing engineering innovation will be solved in the near future.
Grammar improvements: Understanding the differences and similarities between such a path that inventors take and conventionally generated technologies will help us to better appreciate their efforts & the hardships they had to go through in their endeavours.
Understanding the differences and similarities between such a path that inventors take and conventionally generated technologies will help us to better appreciate their efforts & the hardships they have to go through in their endeavors.
Fix grammaticality in this sentence: These planes are not only a mark of development in speed but also in agility.
These planes are a mark of development not only in speed but also in agility.
Fix grammatical errors: Most importantly, we see that these needs of the military were a driving force behind the development and enhancement of the aircraft.
Most importantly, we see that the needs of the military were a driving force behind the development and enhancement of the aircraft.
Fix the grammatical mistakes: Secondly, social factors guided the growth of planes.
Secondly, social factors have guided the growth of planes.
Fix grammar in the sentence: It is noticeable that the size of commercial planes increased over the years in the response to meet the rise in global travelers.
It is noticeable that the size of commercial planes has increased over the years in response to the rise in global travelers.
Fix grammar errors: These modifications were indeed not possible if not for the varying social as well as military requirements during different eras.
These modifications would indeed not have been possible if not for the varying social as well as military requirements during different eras.
Fix errors in this text: When there is a need for something, a technology is create to solve the problem.
When there is a need for something, technology is created to solve the problem.
Improve the grammaticality: This implies that automobile companies had to pull in large sums of money for research and development work to create and promote the sales of such cars.
This implied that automobile companies had to pull in large sums of money for research and development work to create and promote the sales of such cars.
Fix grammar in the sentence: However the cost to finance this project will be high as much research and development have to be done.
However, the cost to finance this project will be high as much research and development have to be done.
Fix grammaticality: As mentioned, the Inconvenient Truth has shown that there is a direct link between carbon emissions and the rising temperatures of the Earth.
As mentioned, the Inconvenient Truth has shown that there is a direct link between carbon emissions and the rising temperatures of the earth.
Fix grammatical errors in this sentence: There many alternative source of energy can be used and applied in our life, such as solar energy, light energy, wind energy, water power and so on.
There are many alternative sources of energy that can be used and applied in our life, such as solar energy, light energy, wind energy, water power, and so on.
Fix grammar: The 21st century is faced with a severe problem of global energy shortage.
The world in the 21st century is faced with the severe problem of global energy shortage.
Fix disfluencies in the sentence: The rate of energy consumption by human is much higher than what nature is able to produce.
However, the rate of energy consumption by humans is much higher than what nature is able to produce.
Fix grammar: Therefore, the last decade has witnessed the increasing energy price due to insufficient supply of energy.
Therefore, the last decade has witnessed increasing energy prices due to an insufficient supply of energy.
Fix grammatical errors in this sentence: In response to energy shortage, engineers design more efficient products and systems.
In response to energy shortage, engineers are designing more efficient products and systems.
Fix grammar in this sentence: Natural movements such as tide, wind and wave can all be used for generating power.
Natural movements such as the tide, the wind, and the waves can all be used for generating power.
Fix grammaticality of the sentence: It shows that nuclear power may gradually replace traditional oil and petroleum.
This shows that nuclear power may gradually replace traditional oil and petroleum.
Fix errors in this text: Although it seems very optimistic that many potential alternative energy resources can be found, there are, in fact, other economic and social constrains faced by engineers.
Although it seems very optimistic that many potential alternative energy resources can be found, there are, in fact, other economic and social constraints faced by engineers.
Fix disfluencies in the sentence: To conclude, engineering design process can be applied to help solve the current problem of global energy shortage.
To conclude, engineering design processes can be applied to help solve the current problem of global energy shortage.
Fix grammatical errors in this sentence: Technologies are always developed to cater certain needs of people, whether to provide better methods of doing things or to develop tools that facilitate working and living.
Technologies are usually developed to cater to certain needs of people, whether to provide better methods of doing things or to develop tools that facilitate working and living.
Fix grammar: Virtual technology has been designed with a series of unique properties to address the observed social needs by engaging a large user population.
Virtual technology was designed with a series of unique properties to address the observed social needs by engaging a large user population.
Improve the grammaticality of this text: New technologies had made people realize the underlying economic opportunities beyond geographic barriers and national boundaries.
New technologies have made people realize the underlying economic opportunities beyond geographic barriers and national boundaries.
Fix grammaticality of the sentence: Catering to this need, a series of solutions has been developed based on virtual technology.
Catering to this need, a series of solutions have been developed based on virtual technology.
Grammar improvements: Apart from the demands from business and education, other factors have also shaped the development of virtual technology and solutions have been designed to meet the needs.
Apart from the demands from business and education, other factors have also shaped the development of virtual technology, and solutions have been designed to meet these needs.
Fix grammaticality: The development of virtual technology is shaped by social factors such as the business environment, educational needs and military demands.
Thus, the development of virtual technology has been shaped by social factors such as the business environment, educational needs, and military demands.
Fix grammar errors: However, problems inevitably generate and affect the process of innovation due to the improper strategies or methods.
However, problems inevitably arise and affect the process of innovation due to improper strategies or methods.
Fix grammatical errors in this sentence: In other words, these designs are produced without adequate market survey, so they turn out to be unwelcomed among public.
In other words, these designs are produced without adequate market survey, so they turn out to be unwelcomed by the public.
Fix grammar: Though the designs are products of fantastic conception, they become useless as rubbish once out of market.
Though the designs are products of fantastic conception, they become useless like rubbish once booted out of the market.
Fix grammar errors in this sentence: After the policy of reform and opening-up, Chinese government has long been encouraging people to make varieties of innovations.
After China adopted the policy of reform and opening up, the Chinese government has long been encouraging people to make varieties of innovations.
Fix errors in this text: As long as the application documents meet the format, the patent will be approved.
As long as the application documents meet the required format, the patent will be approved.
Update to remove grammar errors: Normally the lawsuits of patent infringement can be settled out of court due to the high cost and complicated procedures.
Normally patent infringement lawsuits can be settled out of court due to the high cost and complicated procedures.
Improve the grammar of this text: As a developing country, now China is facing problems on many fields.
As a developing country, China is now facing problems in many fields.
Remove grammatical mistakes: China's education is typical exam-oriented education.
China's education is a typical exam-oriented education.
Fix grammar errors in this sentence: However, the policy of engineering and industry cannot meet the needs.
However, the policy of engineering and industry cannot meet these needs.
Fix grammar: In the technological age, since independent innovation is very important to a nation's development, society needs the people with innovative talent.
In the technological age, since independent innovation is very important to a nation's development, society needs people with innovative talent. |
https://huggingface.co/datasets/grammarly/detexd-benchmark | "), as well as other minority interests and green energy investments. Qurate Retail Group is dedicated to providing a more human way to shop and is the largest player in video commerce (vCommerce), which includes video-driven shopping across linear TV, ecommerce sites, digital streaming, and social platforms. For more information, visit
"As the dynamic audio industry continues to evolve, coupled with the long-overdue warranted attention finally being paid to the influential Black consumer, I am excited to continue collaborating with our outstanding sales teams and Urban One leadership to move the needle forward and drive value for our advertisers, listeners, and users." said Rahmani. "I look forward to further developing the company's revenue streams by leveraging our synergistic audio content offerings, our dominance in authentically connecting with the African American community, and our best-in-class fully integrated, cross-platform advertising solutions across the entire portfolio of Radio One and Reach Media. I am grateful to
"Blender doesn’t care how many vertex groups you have. But MMD does. So the first thing to do is to make sure that we’re not sending MMD more than four weights for any vertex. In Weight Painting mode, select all your vertices, then use the Limit Total Weight Tool. Look in its Operator box below, and make sure that the Limit is 4. This will drop the least weighted vertex groups from any vertices until they have only 4 vertex groups.
"He asked me and the club if we could give him a couple of days off just to clear up his mind and he will be back in the group, I suppose, next Monday, back for training and then be a regular part of the whole squad again," Rangnick said.
"I think a lot of things I heard from the board were about the process and the outline that they were used," said Sunderman. "It seems to be very detailed, very organized and streamlined. They have a lot of different screening tools that maybe some of the other firms didn't talk about as much. Grundmeyer seems to be very focused on the stakeholder survey, and input from all kinds of stakeholders--from community, to staff and students--not just from the board."
"Indeed, my father was right, I loved what I did and I pursued it passionately. Life at CBU came with newly found talents and skills such as on stage spoken word poetry, which I used to share God's Word, basketball, my exercising game and evening straws, my relaxing activity," Bwalya says.
"It was merely a big hall and we did not have an area to prepare medicine or food for the patients. In the cases of isolation, where staff would have to change into their protective gear, we also did not have dedicated areas to do so in the previous set-up," added Vidot.
"Land of Silence" by Tess Afshar, "The Forest of Vanishing Stars" by Kristin Harmel, "The Silent Sister" by Diane Chamberlain, "The Last House on the Street" by Diane Chamberlain, "The Fortune Men" by Nadifa Mohamed, "Anthem" by Noah Hawley, "Hello, Transcriber" by Hanna Morrissey, "Find Me" by Alafair Burker, "No Land to Light On" by Yara Zgheib, "Olga Dies Dreaming" by Xochitl Gonzalez, "The Horsewoman" by James Patterson, "To Paradise" by Hanya Yanagihara.
"Leeds at Elland Road - 22,000. I’ve walked out and the roar… it was unbelievable, it was unreal. Going from non-league to professional football… within three months I’m at Elland road in League One. It was an amazing day… Even though after 12 minutes I tore three ligaments in my ankle, it’s still today an amazing day for me.”
"The Cart.com team is building a platform that can help sellers of all sizes grow faster as the future of commerce becomes increasingly digital," said Rubail Birwadker, Senior Vice President of Global Digital Partnerships at Visa. "As a leader in digital payments, we are excited to continue to partner with Cart.com to put brands in charge of their ecommerce journey and customer relationships."
"Tom was an inspirational leader both on and off the pitch and he helped to shape rugby into the strong and vibrant game it is today. Tom’s life will be reflected upon at our matches this weekend, and his legacy will live long in the history of Irish rugby, may he rest in peace.”
"Travel may be extremely dangerous over the next few days, so we are asking people to stay home, if possible," Col. Joe Gasper, state director of Emergency Management and Homeland Security and director of the Michigan State Police, said in a press release issued Tuesday. "Winter weather is not unexpected in Michigan, but preparing beforehand is the best way to keep you and your family safe."
"We believe Medline's innovative spirit, history of supporting frontline healthcare workers, and belief in improving the patient experience fits well with Lumify's goals," said Scarpone-Lambert. "We know the value that uNight has brought to our own experience as frontline healthcare workers, and we'll continue to work towards every healthcare worker around the world having a uNight Light."
"When you swan off to Dubai in the middle of a pandemic, like they have this past week, and when you push fixtures back 48 hours like they did with us, I've kept really quiet, but I'll tell you something. They went down in my estimation when they did that. We have not resorted to that, but I'll tell you, you can tell them now if they've got Hibs TV on over there, we're still fighting for that second Champions League spot, and they've got to come back to Glasgow and get something, and... and... I'll tell you, honestly, I will love it if we beat them, love it."
"Zeroing in on Zero-Emission Trucks" is based on data gathered from several sources, including market information providers, incentive program records, public press releases, and private correspondence with OEMs (original equipment manufacturers). As there is no centralized accounting of ZETs, it is important to note that figures contained in the report should not be considered static nor should any data on ordered vehicles be
"forward-looking statements" within the meaning of and subject to the safe harbor protections of the Private Securities Litigation Reform Act of 1995. These forward- looking statements are not guarantees of future performance, nor should they be relied upon as representing management's views as of any subsequent date. These statements may include words such as "expect," "estimate," "project," "anticipate," "appear," "believe," "could," "should," "may," "might," "will," "would," "seek," "intend," "probability," "risk," "goal," "target," "objective," "plans," "potential," and similar expressions. Forward-looking statements are statements with respect to the Company's beliefs, plans, expectations, objectives, goals, anticipations, assumptions, estimates, intentions and future performance and are subject to significant known and unknown risks and uncertainties, which could cause the Company's actual results to differ materially from the results discussed in the forward-looking statements. For example, discussions of the effect of our expansion, benefits of the Share Repurchase Plan, trends in asset quality, capital, liquidity, the Company's ability to sell nonperforming assets, expense reductions, planned operational efficiencies and earnings from growth and certain market risk disclosures, including the impact of interest rates, tax reform, inflation and other economic factors are based upon information presently available to management and are dependent on choices about key model characteristics and assumptions and are subject to various limitations. By their nature, certain of the market risk disclosures are only estimates and could be materially different from what actually occurs in the future. Accordingly, our results could materially differ from those that have been estimated. The most recent factor that could cause future results to differ materially from those anticipated by our forward- looking statements include the negative impact of the COVID-19 pandemic and related variants on our business, financial position, operations and prospects, including our ability to continue our business activities in certain communities we serve, the duration of the pandemic and its continued effects on financial markets, a reduction in financial transactions and business activities resulting in decreased deposits and reduced loan originations, increases in unemployment rates impacting our borrowers' ability to repay their loans, our ability to manage liquidity in a rapidly changing and unpredictable market, additional interest rate changes by the Federal Reserve and other government actions in response to the pandemic, including regulations or laws enacted to counter the effects of the COVID-19 pandemic on the economy.
(Manufacturing, Services and Hospital reports) ("ISM ROB") contains information, text, files, images, video, sounds, musical works, works of authorship, applications, and any other materials or content (collectively, "Content") of ISM ("ISM ROB Content"). ISM ROB Content is protected by copyright, trademark, trade secret, and other laws, and as between you and ISM, ISM owns and retains all rights in the ISM ROB Content. ISM hereby grants you a limited, revocable, nonsublicensable license to access and display on your individual device the ISM ROB Content (excluding any software code) solely for your personal, non-commercial use. The ISM ROB Content shall also contain Content of users and other ISM licensors. Except as provided herein or as explicitly allowed in writing by ISM, you shall not copy, download, stream, capture, reproduce, duplicate, archive, upload, modify, translate, publish, broadcast, transmit, retransmit, distribute, perform, display, sell, or otherwise use any ISM ROB Content.
(RED) partners with the most iconic brands and people to create (RED) products and experiences — all of which raise money for the Global Fund, one of the world's largest funders of global health. (RED) partners include Amazon, Anova Culinary, Apple, Balmain, Bank of America, Beats by Dr. Dre, Buffalo Games, Claro, Earth Rated, eos, Girl Skateboards, The Honey Pot Co., KISS Products,
(worth £49), which comes in a bamboo tray, includes 2 giant luxury fruit scones, Farmhouse Biscuits lemon biscuits, a Gold Crown 4” round whisky Dundee cake, Rodda’s clotted cream, Mrs Bridges Scottish strawberry preserve, a traditional English tea tin, Hamlet Gold Box Belgian chocolates and a clotted cream fudge trio slider.
) is a world-leading industrial gases company in operation for over 80 years. Focused on serving energy, environment and emerging markets, the Company provides essential industrial gases, related equipment and applications expertise to customers in dozens of industries, including refining, chemical, metals, electronics, manufacturing, and food and beverage. Air Products is also the global leader in the supply of liquefied natural gas process technology and equipment. The Company develops, engineers, builds, owns and operates some of the world's largest industrial gas projects, including: gasification projects that sustainably convert abundant natural resources into syngas for the production of high-value power, fuels and chemicals; carbon capture projects; and world-scale low- and zero-carbon hydrogen projects supporting global transportation and the energy transition.
). For those of you who do not know what this is, Aspergers is a disorder with traits similar to that of Autism, although milder and without any form of retardation. People with Aspergers suffer from poor social skills, especially vocal tone and body language comprehension and use. They often also have clumsy motor skills, speak in monotone, cannot operate without a rigid timetable, are extra sensitive to bright lights or sounds, and are often obsessed with an obscure topic(such as train timetables for instance).
) think going on a first date on Valentine's Day could be fun. So, Truly wants to help those bold, carefree drinkers get lucky in love by paying for their Valentine's Day first dates. Any adventurous drinkers who slide into their love interests' DMs, send a risky text or call their new boo to make plans for a Valentine's Day first date will get reimbursed by Truly Hard Seltzer.
, "Best Physical Therapy Practice in the Nation" by ADVANCE magazine, Top Workplace in the Nation and has been recognized as a leader in employee volunteering and charitable giving. Our services include physical and occupational/hand therapy, workers' compensation, women's health therapy, concussion management and athletic training. For more information, or to schedule a free assessment in clinic or now online with our virtual free assessments, visit
, "so when we learned of the prospect of A.L. Shilling Spay & Neuter closing its doors, we moved to meet the demand for spay and neuter to ensure that public and private shelters and rescue groups can alter pets before adoption, which is essential to reducing the number of homeless animals being born."
, CEO of Radio One and Reach Media said, "I am excited to formally announce the promotion of Josh Rahmani to Chief Revenue Officer for Radio One stations and Reach Media. Over the past few years, Josh has diligently worked to ensure the alignment of the Radio One corporate sales and Reach Media sales teams to work closer to scale revenue and create opportunities. His team has successfully engaged and worked with many national advertisers to extend their audio marketing across all of our radio assets. Josh has proven himself as a leader who can bring in new and creative revenue opportunities."
, Cash America had entered into a Consent Order with the Consumer Financial Protection Bureau (CFPB) for making loans to covered members of the military or their dependents in violation of the Military Lending Act (MLA), which violations related to debt collection, failure to prevent or timely detect problematic conduct due to inadequate internal compliance, and failure to maintain required records (the "Order"). In the Order, Cash America agreed to cease and desist from the violations and to implement a plan designed to ensure its future compliance with the terms of the Order. The CFPB fined Cash America
, Chief Innovation Officer at Family in Music. "It allows for traditional identification methods to be merged and attached to our NFT structure which is secure and controlled. It is then essential that in case of a dispute that we can reference that identity to a point in time – the point of registering a composition's information and associating it with an off-chain asset.
, Chief Revenue Officer at Playtika, added: "Laurence and his amazing personality and style really brings to life the WSOP player experience. We are proud to have created a commercial that complements the epic persona of Lawrence with the epic legacy of World Series of Poker for the benefit of our players."
, Marathon issued a press release announcing the formation of the Beowulf Joint Venture. That press release represented that the Beowulf Joint Venture was "focused on delivering low cost power to Marathon's Bitcoin mining operations [,]" while also asserting various purported benefits that would flow to Marathon in connection with that joint venture.
, Senior Director Global Environment Health & Safety, commented, "We always strive to provide high-quality of care for our employees and the opportunity to partner with Premise Health on a Digital Wellness Center ensures that employees across the Perrigo organization will now have access to reliable and effective occupational health care or guidance. People are Perrigo's greatest asset, and we believe the virtual occupational health benefits will create a healthier and more productive workforce."
, a Silicon Valley based AI company that provides identity verification solutions, recently announced that they ranked fourth globally for contactless travel of passengers in a tie with the first three algorithms on the National Institute of Standards (NIST) FRVT Paperless Travel leader board. This validates that HyperVerge's facial recognition technology is among the most advanced in the market.
, a nurse who has worked on one of Beverly Hospital's medical-surgical/telemetry floors for 11 years. "New graduate nurses are voicing burnout so soon into their careers and fear for their licenses. Experienced nurses find themselves in constant mourning over the exceptional care they were unable to provide due to no fault of their own. The love for our community and remaining co-workers is what keeps myself and others at the hospital, but the future of this facility lies in the hands of our administration and their willingness to heed our concerns and negotiate appropriate solutions. I'm hoping we can mutually agree that patient safety should always be first priority."
, a survey-based study of digital media usage. With show options covering just about every topic from true crime to travel, there's certainly no shortage of options. To help boil down the offerings, we've crafted a roundup highlighting a few popular programs to choose from. Without further ado, here are 22 podcast shows to consider in 2022.
, and 26D off the Cross Island Parkway. For guests using the Long Island Rail Road, UBS Arena will be accessible to East and Westbound travelers at the Queens Village LIRR station, Eastbound travelers at the brand-new Elmont Station (accessible Westbound in Fall 2022), and via the Belmont Spur station, operating from
, but their size varies anywhere from roughly two to seven inches tall. In addition to being short, bud vases are also narrow or have narrow necks. The width at the neck should be sized so that it fits no more than three or four stems. If you want to display blooms with large, heavy heads, a wide base will offer more stability than a vase that’s narrow all the way down.
, in particular, is in a league of its own. The smart-contract blockchain's native coin ETH has skyrocketed more than 24,000% over the past five years. This type of return was certainly life changing for the lucky ones who were prescient and bold enough to have gotten in at that time.
, is the anchor tenant of the four-story property. The health system recently agreed to a lease extension and expansion that will increase the property's occupancy to 96 percent with a weighted average lease term of more than nine years. Duke Health, the umbrella organization for the broad activities of the
, it has grown into an international center providing peer-to-peer connection, training and development, and career resources for all high-growth professionals. Pavilion is always imagining new ways to help current and future leaders unlock and achieve their professional potential. For more information about Pavilion or to become a member of one of the worldwide chapters, please visit
, now Executive Chairman of Hiro. "From Bitcoin NFTs to unlocking the potential of Bitcoin's massive market cap through DeFi, the projects that our tools have enabled are actively helping the Bitcoin ecosystem to mature. I'm proud to be handing the day-to-day operations of Hiro to Alex, who has been a major driver behind our progress."
, now available from The Freedonia Group, provides historical data (2010, 2015, 2020) and demand forecasts for 2025 and 2030 for unit dose pharmaceutical packaging in millions of US dollars (including inflation) by product type, geographical region, and selected countries. Unit demand for the same years are provided for most product groups.
, rising from 4.1 percent of all medical claim lines in October to 4.4 percent in November. This increase followed a decline of 6.8 percent in October. In November, telehealth utilization also increased in every census region (Midwest, Northeast, South and West), with the greatest increase (8.3 percent) in the Northeast.
, she led the organization, development, and execution of key research initiatives and directed operational efforts supporting digital health institutes and most recently data science response efforts during the first wave of COVID-19. Her work in clinical research supported studies in rare genetic diseases, lab and consumer device validation, skin disorders, Lyme Disease, and precision wellness. Prior to
, the lead author of the study, notes that significant improvements were seen in the incidence, severity, and duration of nerve injuries. Voice and swallowing problems occurred much less commonly, but when they did occur, they resolved in less than half the expected time. "This type of nerve injury, including even short-term vocal dysfunction, has a tremendous impact on patients' physical and psychosocial well-being," said Dr.
, which is being unveiled at the 2022 Kitchen & Bath Industry Show (KBIS) to explore the kitchen as the intersection of personal and planetary health in the American home. Beko's vision is to transform the U.S. industry through expert councils, inspired kitchen designs and buildouts, alliances with like-minded brands like Dole and 35 new cooking, cooling and cleaning products with proprietary technologies and features that empower Americans to lead healthier lives while contributing to a healthier planet.
- Delinquencies up in 1st Quarter, consumers behind on 2.42% of installment loans in 07-Q1, was 2.23% in 06-Q4. Highest rate since 01-Q2, when entered the last recession. Home equity delinquencies rate is up to .60% from .57%. Credit card delinquencies remain at "stratospheric" level. Trend is going in the wrong directions. Less ability to spend means lower sales & profits - possible stock price declines too. See Washington Post:
- I will give thanks to the Lord because of his righteousness; I will sing the praises of the name of the Lord Most High. - As Thanksgiving approaches we can all give thanks to God for everything we have because he is the provider of all things. He has given some more than others according to his will (Luke 12:48 - From everyone who has been given much, much will be demanded
- While a small percentage of folks may move into a 55+ community because of no kids being there (except for grandchildren or others who are visiting), I think a broader view of this issue is that such a community means residents are at similar stages in life and often have more in common with their neighbors than they would in a mixed-use development. For the large majority, jobs are less important and finding friendly folks with like interests are more important. It's not that most residents don't like kids, it's more about maximizing the potential for finding friends.
-Monotonous environment. NY State's types of mountains? Farms of all sorts? Unpolluted lakes? Rolling hills? Trilling streams? Gorges, canyons, waterfalls? Incredible state park system? The Adirondacks? The Hudson? The Great Lakes? A soaring Norway Spruce against the crystal blue sky above the passed storms gasp of fresh snow? Maples ablaze, the first trumpet of daffodil yellow just when you'd begun to doubt if Spring would ever happen again? And all the memories of childhood, family, dreams rooted in the changing, moody seasons? No way. And thus very little opportunity, much less tradition, of getting out and really knowing the world around you. Little opportunity for special, cherished, protected-from-development places to seep into your soul, along with the CHARACTER of the seasons.
. I got caught in one and was worried I was going to get washed off the road. Thunder and lightning hitting all around it was awesome and frightening at the same time. I later did almost get watched off the road going through the Dells...be careful around that area during heavy rain, there was a river right through the road in several places.
. Each day leading up to gameday, AFM will engage different social communities to spread goodness for the chance to win prizes. From engaging with TikTok influencers to targeting pup parents and artists to share how avocados are AlwaysGood, AFM will take over the internet to make it better. Follow the conversation with the hashtag AlwaysGood.
. Moderators are available to assist users with bans and technical issues on the website. PM a moderator (operators in the channel denoted by or % symbols before their name) with all relevant information, including your IP address if banned. Please note: this is a public channel, everything you say here can be logged and repeated elsewhere. Do not release your personal information in the channel!
. What i think has happened here is classic psychosomatic. Youve read the leaflet as you should but for some reason the part about your bowels has impacted you. These are only guidelines but now you have an irrational fear alongside these pills. You imply that youve never had any major problems whilst out, so all i can suggest is that you learn some relaxation techniques and maybe mention it to your gp next time you go. There may be something else he can put you on
/PRNewswire/ -- Inland Pipe Rehabilitation ("IPR"), a portfolio company of investment affiliates of J.F. Lehman & Company ("JFLCO"), announced today the signing of a definitive agreement to acquire Inliner from Granite Construction Incorporated and certain affiliated companies ("Granite"). The acquisition enhances IPR's capabilities and service solutions while expanding its presence throughout
/PRNewswire/ -- Coined the superhero of cereals, Incredi-Bowl is here to save your day, and your breakfast. Whether you're following a Keto lifestyle, looking to cut carbs or just in search of a better way to enjoy your childhood favorites, Incredi-Bowl is the answer with its one, two punch of delicious taste AND variety.
/s4s/ was designed like this before people decided she was a girl. (i was like 'hey it could be a cross between /new/ and /b/ but then 'oh okay, it's just a girl lol'. i just decided to have this design exist as newfag several years later with more news than random)
1ST-Hand-History Foundation (Cultural Attractions- Events- & Facilities; 1641 Northwest Rutter Lane), Video Games Plus (Amusement & Theme Parks; 1143 Northeast Stephens Street), Townsend Electronics (Amusement & Theme Parks; 1949 Southeast Stephens Street), Valley of Indians Bingo Inc (Amusement & Theme Parks; 4388 Old Highway 99 South), Neverland Comics (Amusement & Theme Parks; 150 Northeast Garden Valley Boulevard), River Secrets Guide Svc (Recreational Trips & Guides; 713 W Nebo St).
2 your lighting is weak too. you have absolutely no sense of where is the light coming from, left tit is lit from the right, right tit is lit from the left, same issue with her thighs and calves, the sword gets strong light from the left and her pauldrons get light from the right. and her face is not lit at all.
40-50 MICE DROPPINGS NOTED ON THE PREMISES IN THE FOLLOWING AREAS: SCATTERED ALONG THE BASES OF THE WALLS IN THE KITCHEN, IN THE CLASSROOMS, AND IN STORAGE AREAS ON BOTH SIDES OF THE CLASSROOMS. 1/4 INCH GAP NOTED UNDERNEATH NORTH EXIT DOORS AT FRONT ENTRANCE, 1/4 INCH GAP NOTED UNDERNEATH HANDICAPP ENTRANCE, 1/4 INCH GAP UNDERNEATH STORM DOOR IN DINING AREA AS WELL AS A 1/4 INCH GAP UNDERNATH OUTER EXIT DOOR OF DINING AREA. MUST CLEAN AND SANITIZE ALL AFFECTED AREAS, REPAIR ALL EXIT DOORS AND OUTER OPENINGS AND PROVIDE A CURRENT RECEIPT FROM PEST CONTROL COMPANY. NO CITATION ISSUED
9) The never-ending beehive of activity with traffic clogging up the roads 24/7, and the drivers are soooo scary. You'll get behind a huge cadillac going 8 mph on the highway and you'll swear no one is driving it because you can't even see the head of the 90-year old driver.
: In 1999 – the last year of the 20th century – 17-year-old Bo-ra finds her first love: a sweet, pure but heartbreaking relationship. Years later in the 21st century, news about her first love revives her teenage romance that she once thought had forgotten. 20th Century Girl narrates the lives of the youth in their 20s, filled with vivid moments of love and friendship. Starring the popular Kim You-jung, Byeon Woo-seok, Park Jung-woo, and Roh Yoon-Seo, this pit-a-patting film will be directed by Bang Woo-ri, who won the Best Short Film award for Mrs. Young at the Blue Dragon Awards.
; member of the ACS Board of Regents; and a former member of the Biden Cancer Initiative, who attended Wednesday's announcement at the White House. "Surgeons play an essential role in the effort to end cancer as we know it through our surgery, our research, and our constant pursuit of innovation to find cures."
; the number of scholarships and dollar amounts awarded may vary each year and are determined by the Education Foundation's Board of Directors. Criteria to be considered include, but aren't limited to the following: academic achievements, financial need, relationship to the Realtor family, and contributions to family, school and community. The Foundation's Board of Directors has "sole and absolute discretion" over all decisions as to whether an applicant qualifies.
> three problems there: 1) he's actively looking for a way out the whole time he's been here, nosing into my shit and jumping all over everything, 2) I have nothing remotely close to cat care supplies, all the stores to get that stuff near me are closed now, and I probably couldn't travel with him in my car, and 3) he isn't neutered, he's rubbing his fuzzy, intact little cat nuts all over my carpet, and he's already sprayed a bit once
>"let the meats touch" means show them interacting; the fat of the upper leg should be pushed by the lower leg. (the lower leg would also be pushed by the floor, but idk if you want her that chubby). You can show that very easily by actually drawing the curve of the leg a bit flatter; it's like the curve is interrupted.
>>Wife has a 'hothusband' fetish, which apparently is the same thing as a Cuckquean fetish if they're not into the humiliation part of it. >>To her one on of the hottest things in the world is me busting a nut in another woman, then fucking her raw while the other woman's pussy juices are still on my cock.
>Chuu: If I had a younger sister, I’d like to have one who’s like Gowon. One whom I’d want to take great care of and teach things to or learn from. On a cloudy day, I’ll find you and go to a forest. That’ll brighten me up immediately, you have that kind of energy. I may seem like a childish unnie but I’ll try to become a good unnie for you. I love you~ this is awkward ㅎㅎ
>Frequently someone writes to ask me if I can give them the name of a story, which they think I may have written, and tell them where to find it. They don't remember the title but when they describe the story it is invariably 'The Last Question'. This has reached the point where I recently received a long-distance phone call from a desperate man who began, "Dr. Asimov, there's a story I think you wrote, whose title I can't remember—" at which point I interrupted to tell him it was 'The Last Question' and when I described the plot it proved to be indeed the story he was after. I left him convinced I could read minds at a distance of a thousand miles.
>George Orwell’s Animal Farm examines the insidious ways in which public officials can abuse their power, as it depicts a society in which democracy dissolves into autocracy and finally into totalitarianism. From the Rebellion onward, the pigs of Animal Farm use violence and the threat of violence to control the other animals. However, while the attack dogs keep the other animals in line
>The second in the popular series! In order to fulfill her son's plea, the mother enters into a physical relationship with a man on the condition that it be her last. But it won't be just sex, and the man will fuck her to her heart's content! Will she be able to return safely to her beloved son?
A HAPE world has been created to merge fashion, the NFT community and the metaverse. The hotly anticipated HAPEWALK, a brand new metaverse concept core to the HAPE brand, will offer a new space for collaborations and brand extensions – several major luxury fashion houses have already approached the brand for collaboration.
A friend i know who actually knows his shit told me to think boxes to help me. But I don't know if I've been memed or not, given that the minecraft steve guy down there seems wonky aswell expecially his right arm and the weapons (I picked a skitarii because I've painted hundreds of them and I tought familiarity with its shapes and details would've helped me understand how it is).
A friend of mine has been underweight for ten years and suffered with ammenorhea all that time however even though she has not put weight on her periods came back out of the blue a couple of years ago. Another friend of mine was a normal weight for a year and a half before hers started again. So there is no hard and fast rule. With regards to fertility, well again everyone is different, again, you would probably have to go through fertility tests to see if your ED has affected it. If you are worried you can ask your GP for an ovarian scan, to see what is happening.
A lead plaintiff is a representative party who acts on behalf of all class members in directing the litigation. The lead plaintiff is usually the investor or small group of investors who have the largest financial interest and who are also adequate and typical of the proposed class of investors. The lead plaintiff selects counsel to represent the lead plaintiff and the class and these attorneys, if approved by the court, are lead or class counsel. Your ability to share in any recovery is not affected by the decision of whether or not to serve as a lead plaintiff.
A lead plaintiff is a representative party who acts on behalf of all class members in directing the litigation. The lead plaintiff is usually the investor or small group of investors who have the largest financial interest and who are also adequate and typical of the proposed class of investors. The lead plaintiff selects counsel to represent the lead plaintiff and the class and these attorneys, if approved by the court, are lead or class counsel. Your ability to share in any recovery is not affected by the decision of whether or not to serve as a lead plaintiff.
A long stretch of states from New Mexico to Maine remained under winter storm warnings and watches and the path of the storm stretched further from the central U.S. into more of the South and Northeast. Heavy snow was expected from the southern Rockies to northern New England, while forecasters said heavy ice buildup was likely from Texas to Pennsylvania.
A picture taken on 3 February 2022 in the village of Jinderes in the Afrin region of Syria's rebel-held northern Aleppo province shows the remains of a US helicopter following an overnight raid by US special operations forces against suspected jihadists in the Syrian norwestern province of Idlib. Photo: Rami al SAYED / AFP
A question for you: I'm starting out in Koikatsu and am wondering how to edit character models in greater detail. I want to make monster girls, like with four arms or eyes, or a mermaid; but the program seems to only let you do stuff with the sliders. Is there a way to get it to work like Source Filmmaker where you can shrink certain parts away and put various props together to "build" the character?
A situation which I clearly recall was when I tried to commit suicide in the ladies loo. I don't know how long I been in the loo but eventually, I was bombarded by a load of flapping nurses and a tough support worker, berating me for what I had attempted to do. There was very little empathy or indeed support from the staff involved. I was made to feel like a 'naughty schoolgirl'.
A summary: In the previous set she was herself the whole time(until green hypnos her with the pink light). He will reset the memories of his friends and blue until before he fucked her(so until she accepts to be part of the photo club). And the second set is just full slutty hypno blue fuck session.
A wristwatch commemorating Richardson’s world record was found at the plane crash site in the spring of 1959 after the snow melted, along with a dice and a pair of Holly’s notable glasses. But not everything was returned, and family members are praying that a few items will turn up as more awareness of Richardson goes public.
ABB C1 offers a unique postbiotic-based solution that provides a holistic approach featuring optimized immune innate response, accelerated natural adaptive immune reaction and controlled hyperreactivity events such as poor short-term results or longer COVID-19 symptoms. Combining beta glucans with selenium and zinc delivered through yeast fermentation, ABB C1's breakthrough innovation closes the gap between innate and adaptive immunity by empowering both and offers a synergistic effect unmatched in the industry. The product is available in stick packs, capsules, tablets, gummies and bulk powder.
AI is an amazingly useful tool. But it basically works by amassing vast quantities of data points about our human activity, looking for correlations and then extrapolating into the future. And there are limitations to doing that. If you’re looking for data points about what we do and say, you tend to ignore social silences because what we don’t say by definition doesn’t get recorded. Secondly, correlation is not causation: you can’t understand why people are doing things if you assume that everything can be judged just by looking at correlations and data points. Thirdly, context change, which means that what happened in the recent past doesn’t always reflect what’s going to happen in the future.
According to a person with knowledge of the decision, no offer of the job was made to Harbaugh. The person spoke to the AP on condition of anonymity because details of the process were not being made public by the university or the team. The Vikings also informed the two other finalists, Rams defensive coordinator Raheem Morris and New York Giants defensive coordinator Patrick Graham, that they won’t be selected, the person said.
Ace will be introducing the newly designed and exclusive indigo Weber Genesis SA-E-325s. The biggest grilling innovation in decades, that creates a full backyard culinary experience. Showcasing advanced features like heavy-duty 9mm stainless steel cooking grates, three-burner liquid propane, Weber's largest and hottest sear zone and expandable top cooking grate, with the Ace exclusive Indigo color lid and doors. It allows grillers to cook a full restaurant-quality meal outside, featuring proprietary PureBlu burners designed to provide a consistent and precise heat with an efficient, even flame.
Actually I think (I may be wrong in the number) in one part of the manga it's said that Espada has already had over a 100 partners already. It's implied she molested/made up with more than half of the last school she was at but since she was pretty powerful, nobody questioned it. But still a virgin lol.
Actually, I found an archive of what I was looking for, though I'd take any others people are aware of, likewise, any guides specifically for this kind of stuff or tips? I'm pretty new to editing in general, so I mean stuff like blending, making the colors look more natural, etc. I use gimp
Actually, I would say they are very equal--if anything, I would give the slightly more upscale nod to Mabry. Remember, Mabry includes all of the neighborhoods on and surrounding Sweat Mountain and its corresponding highlands and big ridges--which is the "northern" East Cobb equivalent to the Chattahoochee River in "southern" East Cobb (this is the Dickerson district, with some of the river area attending East Cobb Middle).
Adding 20+ live-learning courses to the existing catalog of 13, covering topics from CEO School to Marketing School to a Cold Calling Course. In partnership with Docebo, Pavilion will also begin offering 200+ video-based, on-demand courses allowing members the option of self-directed learning and a chance to hone in on key skills.
Additionally, while containing some of Chicago's most notable cultural institutions, there are a number of other interesting areas in the neighborhood. The park and lakefront offer spectacular scenery for rollerblading, skating, bicycling and picnics. Oz Park is also located here, named after the author L. Frank Baum, the park contains statues of the Tin Man, Scarecrow, Cowardly Lion, Toto and Dorothy, who welcomes visitors to the "Emerald Garden'', and the park, has "Dorothy's Sandlot'', which is appealing to children. From May through the month of October, popular attractions are the Lincoln Park Farmers Market and the Green City Market.
Ah I don't want you to feel bad, I've just always been nervous about posting wip's and somebody posting a redraw/redline, posting their edit to their socials, and then I get accused of copying them. This exact thing happened to me years ago and it fucking sucked. Unfortunately since you have a much bigger following people will definitely think that I copied you.
Alexander was convicted in December of second-degree murder, leaving the scene of a fatal accident and evidence tampering in the the girl’s death. Prosecutors presented evidence in her trial showing that Alexander had several drinks before leaving a bar in Lansing and driving to Leavenworth, where she hit Lynch around 2 a.m. on Aug. 7, 2021.
All I want to know is what's wrong with me and how I can fix it. I started being treated for depression 10 yrs ago and I have never felt this way before. People keep asking me if I'm still taking my meds, which I am but things have changed now. I don't think depression is the problem anymore or the main problem anyway. If all these thoughts would go away I could concentrate on the depression, but feeling like everyone is watching me and talking,laughing about me is getting in the way. If I knew what was wrong and how to fix it I would have a bit of hope, at the moment I can't see an end to this.
All parts of the food establishment and all parts of the property used in connection with the operation of the establishment shall be kept neat and clean and should not produce any offensive odors. REMOVE UNUSED EQUIPMENT AND UNNECESSARY ARTICLES IN STORAGE AREAS TO PREVENT PEST HARBORAGE. SEPARATE CLEANING EQUIPMENT FROM FOOD AND DRINK IN KITCHEN.
All that is all that was all that ever could be and all that cannot ever be, everything that is there to know and not know, everything that is there to feel and not feel, everything that is there to experience and not experience in a single moment, life is amazing. This is just a little price to pay for .. Emm.. Setting things up... So that you can enjoy the show later. This is not limited to human stuff, you just feel this light and you wouldn't want anything else anymore, you are that light and then this stupid body pulls you back into this hellhole saying 'enough for now, go do your job'
Also read - Our Privacy Policy | ZimEye is a spread out media-network market of professionals in various fields that include arts & journalism as practiced by many of its subscribers scattered across the globe. The objective is to expose at close range facts, myths, commentaries, and news-centric developments on Zimbabwe and Africa at large.
Also why would you leave a charming area like Saratoga for an overpopulated sprawling area with little or no character or history at all? In Florida they build buildings to mimic the architecture of the north (the Saratoga Springs resort at Disney World comes to mind). Doesn't make sense to me. no matter where you live there are issues. Visiting a place for a week or two on vacation does not mean you will like to live there year round. Think very carefully before you make a move. Jay
Also, with the June 15th start date, you're correct that people start wishing for rain in June, which very rarely happens since June is the driest month of the year on average. Even when the monsoon is fully established, it's still not a guarantee that there will be rain ... in fact, some places in & around Phoenix, and much of the western part of AZ might have no rain all summer. We should be more focused the
Although this is off-topic the idea that voices lie I find a bit alien to me. My voices told me to look to the Bible to back up what they were saying, and it matched, word-for-word, what they said. This is one of the reasons I believe my psychosis is God the Father speaking to me, through His Holy Spirit, and subsequently His Son (and not the Holy Spirit).
Americans are so weak, they can't handle any criticism of any aspect of America. Even something dumb like their plastic faux architecture that looks fake and cheap. Plenty of things America does right but contemporary architecture isn't one of them. if you want a Tuscan villa then move to Tuscany. don't waste your money on some high fructose corn syrup imitation that is tacky as fuck
Amgen is one of the 30 companies that comprise the Dow Jones Industrial Average and is also part of the Nasdaq-100 index. In 2021, Amgen was named one of the 25 World's Best Workplaces™ by Fortune and Great Place to Work™ and one of the 100 most sustainable companies in the world by Barron's. |
https://huggingface.co/wanyu | models 5
wanyu/R3-Binary-Classifier
Text Classification • Updated Dec 16, 2022 • 2
wanyu/R3-Intent-Classifier
Text Classification • Updated Dec 16, 2022 • 4
wanyu/IteraTeR-ROBERTA-Intention-Classifier
Text Classification • Updated Apr 4, 2022 • 6 • 3
wanyu/IteraTeR-BART-Revision-Generator
Text2Text Generation • Updated Apr 4, 2022 • 7
wanyu/IteraTeR-PEGASUS-Revision-Generator
Text2Text Generation • Updated Apr 4, 2022 • 23 • 2 |
https://huggingface.co/machineteacher | 7 7 1
Vipul Raheja
machineteacher
vipulraheja
Research interests
None yet
Organizations
Papers 1
arxiv:2305.09857
models
None public yet
datasets
None public yet |
https://huggingface.co/fqyd-yxfw | Yichen Mo
fqyd-yxfw
Research interests
None yet
Organizations
models
None public yet
datasets
None public yet |
https://huggingface.co/syavnyi | Serhii Yavnyi
syavnyi
Research interests
None yet
Organizations
models
None public yet
datasets
None public yet |
https://huggingface.co/lynazhang | Li Lyna Zhang
lynazhang
Lynazhang
Research interests
None yet
Organizations
Papers 3
arxiv:2303.08308
arxiv:2303.09730
arxiv:2306.14393
models
None public yet
datasets
None public yet |
https://huggingface.co/ddhruvkr | 1
Dhruv Kumar
ddhruvkr
ddhruvkr
ddhruvkr
Research interests
None yet
Organizations
models
None public yet
datasets
None public yet |
https://huggingface.co/skurzhanskyi | Oleksandr Skurzhanskyi
skurzhanskyi
Research interests
None yet
Organizations
models
None public yet
datasets
None public yet |
https://huggingface.co/apurvajoshi | Apurva Joshi
apurvajoshi
https://joshiapurva.com/
apurvjoshi
apurvajoshi
Research interests
None yet
Organizations
models
None public yet
datasets
None public yet |
https://huggingface.co/knarhov | Knar Hovakimyan
knarhov
Research interests
None yet
Organizations
models
None public yet
datasets
None public yet |
https://huggingface.co/dimalik | dimi alik
dimalik
Research interests
None yet
Organizations
models
None public yet
datasets
None public yet |
https://huggingface.co/stuwest | Stu West
stuwest
stuwest
Research interests
None yet
Organizations
models
None public yet
datasets
None public yet |
https://huggingface.co/osliusarenko | Oleksii Sliusarenko
osliusarenko
Research interests
None yet
Organizations
models
None public yet
datasets
None public yet |
https://huggingface.co/Jade38 | Razzaghi
Jade38
Research interests
None yet
Organizations
models
None public yet
datasets
None public yet |
https://huggingface.co/gunnarlund | Gunnar Lund
gunnarlund
Research interests
None yet
Organizations
models
None public yet
datasets
None public yet |
https://huggingface.co/swinig | Swini Garimella
swinig
Research interests
None yet
Organizations
models
None public yet
datasets
None public yet |
https://huggingface.co/viveksck86 | Vivek Kulkarni
viveksck86
Research interests
Natural Language Processing
Organizations
models
None public yet
datasets
None public yet |
https://huggingface.co/edjez | Eduardo Jezierski PRO
edjez
Research interests
AI tooling, transformer models, privacy, bias & fairness, RL
Organizations |
https://huggingface.co/marknorrisgrammarly | Mark Norris
marknorrisgrammarly
Research interests
None yet
Organizations
models
None public yet
datasets
None public yet |
https://huggingface.co/anmiko | Andriy Gryshchuk
anmiko
Research interests
None yet
Organizations
models
None public yet
datasets
None public yet |
https://huggingface.co/jaalvare | Javier Alvarez Valle
jaalvare
javier-alvarez
Research interests
None yet
Organizations
models
None public yet
datasets
None public yet |
https://huggingface.co/shuc-grammarly | Shu C
shuc-grammarly
Research interests
None yet
Organizations
models
None public yet
datasets
None public yet |
https://huggingface.co/a-chernodub | Artem Chernodub
a-chernodub
a.chernodub
Research interests
None yet
Organizations
models
None public yet
datasets
None public yet |
https://huggingface.co/Awettreich | 1
Alex Wettreich
Awettreich
Research interests
None yet
Organizations
models
None public yet
datasets
None public yet |
https://huggingface.co/olexandrkorniienko | Oleksandr Korniienko
olexandrkorniienko
Research interests
None yet
Organizations
models
None public yet
datasets
None public yet |
https://huggingface.co/Rohan3181 | 1
Rohan
Rohan3181
Research interests
None yet
Organizations
models
None public yet
datasets
None public yet |
https://huggingface.co/dransom90 | 1
DJ Ransom
dransom90
dransom90
Research interests
None yet
Organizations
models
None public yet
datasets
None public yet |
https://huggingface.co/dmytro-writer | 1
Dmytro M
dmytro-writer
Research interests
None yet
Organizations
models
None public yet
datasets
None public yet |
https://huggingface.co/sanyunamome | 1
Sanyu Namome
sanyunamome
Research interests
None yet
Organizations
models
None public yet
datasets
None public yet |
https://huggingface.co/pklugman | 1
Phillip
pklugman
Research interests
None yet
Organizations
models
None public yet
datasets
None public yet |
https://huggingface.co/samuchan | 1
Sam Chan
samuchan
Research interests
None yet
Organizations
models
None public yet
datasets
None public yet |
https://huggingface.co/breona | 1
breona blanton
breona
Research interests
None yet
Organizations
models
None public yet
datasets
None public yet |
https://huggingface.co/SWilliamsWriter | 1
Spencer Williams
SWilliamsWriter
Research interests
None yet
Organizations
models
None public yet
datasets
None public yet |
https://huggingface.co/eszuhany | Eric Szuhany
eszuhany
Research interests
None yet
Organizations
models
None public yet
datasets
None public yet |
https://huggingface.co/spaces/Writer/Paste-to-Markdown | App Files Files Community |
https://huggingface.co/spaces/Writer/instruct-palmyra-20b | App Files Files
Community
1 |
https://huggingface.co/spaces/Writer/token-counter | App Files Files Community |
https://huggingface.co/mattsobel | 1
matt sobel
mattsobel
Research interests
None yet
Organizations
models
None public yet
datasets
None public yet |
https://huggingface.co/blu | 1
Lukas Beisteiner
blu
lukasbeisteiner
lbeisteiner
Research interests
None yet
Organizations
models
None public yet
datasets
None public yet |
https://huggingface.co/amelenty | Ada Melentyeva
amelenty
Research interests
None yet
Organizations
models
None public yet
datasets
None public yet |
https://huggingface.co/Writer/palmyra-small | Palmyra Small 128M
|||
Model Description
Palmyra Small was primarily pre-trained with English text. Note that there is still a trace amount of non-English data present within the training corpus that was accessed through CommonCrawl. A causal language modeling (CLM) objective was utilized during the process of the model's pretraining. Similar to GPT-3, Palmyra Small is a member of the same family of models that only contain a decoder. As a result, it was pre-trained utilizing the objective of self-supervised causal language modeling. Palmyra Small uses the prompts and general experimental setup from GPT-3 in order to conduct its evaluation per GPT-3.
Use case
Palmyra Small is the fastest of Writer’s LLMs and can perform important tasks such as text parsing, simple classification, address correction, and keyword recognition. Providing more context drives even better performance.
Training data
Palmyra Small (128M) was trained on Writer’s custom dataset.
Intended Use and Limitations
Palmyra Small learns an inner representation of the English language that can be used to extract features useful for downstream tasks. However, the model is best at what it was pre-trained for which is generating text from a prompt.
How to use
This model can be easily loaded using the AutoModelForCausalLM functionality:
import torch from transformers import AutoModelForCausalLM, AutoTokenizer model = AutoModelForCausalLM.from_pretrained("Writer/palmyra-small") tokenizer = AutoTokenizer.from_pretrained("Writer/palmyra-small")
Limitations and Biases
Palmyra Small’s core functionality is to take a string of text and predict the next token. While language models are widely used for other tasks, there are many unknowns in this work. When prompting Palmyra, keep in mind that the next statistically likely token is not always the token that produces the most "accurate" text. Never rely on Palmyra Small to produce factually correct results.
Palmyra Small was trained on Writer’s custom data. As with all language models, it is difficult to predict how Palmyra Small will respond to specific prompts, and offensive content may appear unexpectedly. We recommend that the outputs be curated or filtered by humans before they are released, both to censor undesirable content and to improve the quality of the results.
Citation and Related Information
To cite this model:
@misc{Palmyra, author = {Writer Engineering Team}, title = {{Palmyra-base Parameter Autoregressive Language Model}}, howpublished = {\url{https://dev.writer.com}}, year = 2023, month = January } |
https://huggingface.co/Writer/InstructPalmyra-20b | InstructPalmyra-20b
Developed by: https://writer.com/;
Model type: Causal decoder-only;
Language(s) (NLP): English;
License: Apache 2.0;
Finetuned from model: Palmyra-20B.
Model Description
Introducing InstructPalmyra-20b, a state-of-the-art instruction-following 20b language model designed to deliver exceptional performance and versatility. Derived from the foundational architecture of Palmyra-20b, InstructPalmyra-20b is specifically tailored to address the growing demand for advanced natural language processing and comprehension capabilities.
The InstructPalmyra-20b model is meticulously trained on an extensive dataset of approximately 70,000 instruction-response records. These records are generated by our dedicated Writer Linguist team, who possess considerable expertise in language modeling and fine-tuning techniques. By leveraging their skills and knowledge, the InstructPalmyra-20b model is primed to offer unparalleled proficiency in understanding and executing language-based instructions.
One of the key differentiators of InstructPalmyra-20b lies in its ability to process complex instructions and generate accurate, contextually appropriate responses. This makes it an ideal choice for a wide range of applications, including virtual assistants, customer support, content generation, and more. Additionally, the model's comprehensive training enables it to adapt and perform well under varying conditions and contexts, further expanding its potential use cases.
Usage :
import torch from transformers import AutoTokenizer, AutoModelForCausalLM model_name = "Writer/InstructPalmyra-20b" tokenizer = AutoTokenizer.from_pretrained(model_name) model = AutoModelForCausalLM.from_pretrained( model_name, device_map="auto", torch_dtype=torch.float16 ) instruction = "Describe a futuristic device that revolutionizes space travel." PROMPT_DICT = { "prompt_input": ( "Below is an instruction that describes a task, paired with an input that provides further context. " "Write a response that appropriately completes the request\n\n" "### Instruction:\n{instruction}\n\n### Input:\n{input}\n\n### Response:" ), "prompt_no_input": ( "Below is an instruction that describes a task. " "Write a response that appropriately completes the request.\n\n" "### Instruction:\n{instruction}\n\n### Response:" ), } text = ( PROMPT_DICT["prompt_no_input"].format(instruction=instruction) if not input else PROMPT_DICT["prompt_input"].format(instruction=instruction, input=input) ) model_inputs = tokenizer(text, return_tensors="pt").to("cuda") output_ids = model.generate( **model_inputs, max_length=256, ) output_text = tokenizer.batch_decode(output_ids, skip_special_tokens=True)[0] clean_output = output_text.split("### Response:")[1].strip() print(clean_output)
It can also be used with text-generation-inference
model=Writer/InstructPalmyra-20b volume=$PWD/data docker run --gpus all --shm-size 1g -p 8080:80 -v $volume:/data ghcr.io/huggingface/text-generation-inference --model-id $model
Limitations and Biases
InstructPalmyra's core functionality is to take a string of text and predict the next token. While language models are widely used for other tasks, there are many unknowns in this work. When prompting InstructPalmyra, keep in mind that the next statistically likely token is not always the token that produces the most "accurate" text. Never rely on InstructPalmyra to produce factually correct results.
InstructPalmyra was trained on Writer’s custom data. As with all language models, it is difficult to predict how InstructPalmyra will respond to specific prompts, and offensive content may appear unexpectedly. We recommend that the outputs be curated or filtered by humans before they are released, both to censor undesirable content and to improve the quality of the results.
Uses
Out-of-Scope Use
Production use without adequate assessment of risks and mitigation; any use cases which may be considered irresponsible or harmful.
Bias, Risks, and Limitations
InstructPalmyra-20b is mostly trained on English data, and will not generalize appropriately to other languages. Furthermore, as it is trained on a large-scale corpora representative of the web, it will carry the stereotypes and biases commonly encountered online.
Recommendations
We recommend users of InstructPalmyra-20b to develop guardrails and to take appropriate precautions for any production use.
Citation and Related Information
To cite this model:
@misc{InstructPalmyra, author = {Writer Engineering team}, title = {{InstructPalmyra-20b : Instruct tuned Palmyra-Large model}}, howpublished = {\url{https://dev.writer.com}}, year = 2023, month = Augest }
||| |
https://huggingface.co/vklimkov | Viacheslav Klimkov
vklimkov
Research interests
None yet
Organizations
models
None public yet
datasets
None public yet |
https://huggingface.co/Writer/palmyra-base | Palmyra Base 5B
|||
Model Description
Palmyra Base was primarily pre-trained with English text. Note that there is still a trace amount of non-English data present within the training corpus that was accessed through CommonCrawl. A causal language modeling (CLM) objective was utilized during the process of the model's pretraining. Similar to GPT-3, Palmyra Base is a member of the same family of models that only contain a decoder. As a result, it was pre-trained utilizing the objective of self-supervised causal language modeling. Palmyra Base uses the prompts and general experimental setup from GPT-3 in order to conduct its evaluation per GPT-3.
Use case
Palmyra Base is extremely powerful while being extremely fast. This model excels at many nuanced tasks such as sentiment classification and summarization.
Training data
Palmyra Base (5b) was trained on Writer’s custom dataset.
Intended Use and Limitations
Palmyra Base learns an inner representation of the English language that can be used to extract features useful for downstream tasks. However, the model is best at what it was pre-trained for which is generating text from a prompt.
How to use
This model can be easily loaded using the AutoModelForCausalLM functionality:
from transformers import AutoModelForCausalLM, AutoTokenizer import torch model = AutoModelForCausalLM.from_pretrained("Writer/palmyra-base", torch_dtype=torch.float16).cuda() # the fast tokenizer currently does not work correctly tokenizer = AutoTokenizer.from_pretrained("Writer/palmyra-base", use_fast=False)
Limitations and Biases
Palmyra Base’s core functionality is to take a string of text and predict the next token. While language models are widely used for other tasks, there are many unknowns in this work. When prompting Palmyra Base, keep in mind that the next statistically likely token is not always the token that produces the most "accurate" text. Never rely on Palmyra Base to produce factually correct results.
Palmyra Base was trained on Writer’s custom data. As with all language models, it is difficult to predict how Palmyra Base will respond to specific prompts, and offensive content may appear unexpectedly. We recommend that the outputs be curated or filtered by humans before they are released, both to censor undesirable content and to improve the quality of the results.
Evaluation results
Evaluation of Palmyra-base model on the SuperGLUE benchmark
Task Metric Value
boolq acc 64.43
cb acc 10.71
f1 08.32
copa acc 76.00
multirc acc 01.26
record f1 84.02
em 83.29
wic acc 50.00
wsc acc 36.54
Citation and Related Information
To cite this model:
@misc{Palmyra, author = {Writer Engineering team}, title = {{Palmyra-base Parameter Autoregressive Language Model}}, howpublished = {\url{https://dev.writer.com}}, year = 2023, month = January } |
https://huggingface.co/Writer/palmyra-3B | Palmyra 3B
|||
Model Description
Palmyra 3B was primarily pre-trained with English text. Note that there is still a trace amount of non-English data present within the training corpus that was accessed through CommonCrawl. A causal language modeling (CLM) objective was utilized during the process of the model's pretraining. Similar to GPT-3, Palmyra 3B is a member of the same family of models that only contain a decoder. As a result, it was pre-trained utilizing the objective of self-supervised causal language modeling. Palmyra 3B uses the prompts and general experimental setup from GPT-3 in order to conduct its evaluation per GPT-3.
Use case
Palmyra 3B is the fastest of Writer’s LLMs and can perform important tasks such as text parsing, simple classification, address correction, and keyword recognition. Providing more context drives even better performance.
Training data
Palmyra 3B was trained on Writer’s custom dataset.
Intended Use and Limitations
Palmyra 3B learns an inner representation of the English language that can be used to extract features useful for downstream tasks. However, the model is best at what it was pre-trained for which is generating text from a prompt.
How to use
This model can be easily loaded using the AutoModelForCausalLM functionality:
from transformers import AutoModelForCausalLM, AutoTokenizer model = AutoModelForCausalLM.from_pretrained("Writer/palmyra-3B") tokenizer = AutoTokenizer.from_pretrained("Writer/palmyra-3B")
Limitations and Biases
Palmyra 3B core functionality is to take a string of text and predict the next token. While language models are widely used for other tasks, there are many unknowns in this work. When prompting Palmyra, keep in mind that the next statistically likely token is not always the token that produces the most "accurate" text. Never rely on Palmyra 3B to produce factually correct results.
Palmyra 3B was trained on Writer’s custom data. As with all language models, it is difficult to predict how Palmyra 3B will respond to specific prompts, and offensive content may appear unexpectedly. We recommend that the outputs be curated or filtered by humans before they are released, both to censor undesirable content and to improve the quality of the results.
Citation and Related Information
To cite this model:
@misc{Palmyra, author = {Writer Engineering Team}, title = {{Palmyra 3B Parameter Autoregressive Language Model}}, howpublished = {\url{https://dev.writer.com}}, year = 2023, month = March } |
https://huggingface.co/Writer/palmyra-large | Palmyra Large 20B
Palmyra-Large is a 20B parameters causal decoder-only model built by Writer and trained on +800B tokens of Palmyra-Index-Data enhanced with curated corpora.
|||
Model Details
Palmyra Large was primarily pre-trained with English text. Note that there is still a trace amount of non-English data present within the training corpus that was accessed through CommonCrawl. A causal language modeling (CLM) objective was utilized during the process of the model's pretraining. Similar to GPT-3, Palmyra Large is a member of the same family of models that only contain a decoder. As a result, it was pre-trained utilizing the objective of self-supervised causal language modeling.
Model Description
Developed by: https://www.writer.com;
Model type: Causal decoder-only;
Language(s) (NLP): English (and limited capabilities in German, Spanish, French, Swedish);
License: Apache 2.0 license.
Uses
Direct Use
Research on large language models; as a foundation for further specialization and finetuning for specific usecases (e.g., summarization, text generation, chatbot, etc.)
Out-of-Scope Use
Production use without adequate assessment of risks and mitigation; any use cases which may be considered irresponsible or harmful.
Bias, Risks, and Limitations
Palmyra-large-20B is trained mostly on English with limited capabilities also in German, Spanish, French, Swedish. It will not generalize appropriately to other languages. Furthermore, as it is trained on a large-scale corpora representative of the web, it will carry the stereotypes and biases commonly encountered online.
Recommendations
We recommend users of Palmyra-Large-20B to consider finetuning it for the specific set of tasks of interest, and for guardrails and appropriate precautions to be taken for any production use.
Use case
Palmyra Large is extremely powerful while being extremely fast. This model excels at many nuanced tasks such as sentiment classification and summarization.
Training data
Palmyra Large (20b) was trained on Writer’s custom dataset.
Intended Use and Limitations
Palmyra Large learns an inner representation of the English language that can be used to extract features useful for downstream tasks. However, the model is best at what it was pre-trained for which is generating text from a prompt.
How to use
This model can be easily loaded using the AutoModelForCausalLM functionality:
import os from transformers import AutoModelForCausalLM, AutoTokenizer # set HF environment variable auth_token = os.environ.get("HF_TOKEN", True) model = AutoModelForCausalLM.from_pretrained( "Writer/palmyra-large", device_map="auto", torch_dtype=torch.float16, use_auth_token=auth_token, ) tokenizer = AutoTokenizer.from_pretrained( "Writer/palmyra-large", use_auth_token=auth_token )
It can also be used with text-generation-inference
model=Writer/palmyra-large volume=$PWD/data docker run --gpus all --shm-size 1g -p 8080:80 -v $volume:/data ghcr.io/huggingface/text-generation-inference --model-id $model
Limitations and Biases
Palmyra Large’s core functionality is to take a string of text and predict the next token. While language models are widely used for other tasks, there are many unknowns in this work. When prompting Palmyra Large, keep in mind that the next statistically likely token is not always the token that produces the most "accurate" text. Never rely on Palmyra Large to produce factually correct results.
Palmyra Large was trained on Writer’s custom data. As with all language models, it is difficult to predict how Palmyra Large will respond to specific prompts, and offensive content may appear unexpectedly. We recommend that the outputs be curated or filtered by humans before they are released, both to censor undesirable content and to improve the quality of the results.
Citation and Related Information
To cite this model:
@misc{Palmyra, author = {Writer Engineering team}, title = {{Palmyra-Large Parameter Autoregressive Language Model}}, howpublished = {\url{https://dev.writer.com}}, year = 2023, month = March }
Contact
Hello@writer.com |
https://huggingface.co/Writer/camel-5b-hf | Camel 🐪 5B
Model Description
Introducing Camel-5b, a state-of-the-art instruction-following large language model designed to deliver exceptional performance and versatility. Derived from the foundational architecture of Palmyra-Base, Camel-5b is specifically tailored to address the growing demand for advanced natural language processing and comprehension capabilities.
The Camel-5b model is meticulously trained on an extensive dataset of approximately 70,000 instruction-response records. These records are generated by our dedicated Writer Linguist team, who possess considerable expertise in language modeling and fine-tuning techniques. By leveraging their skills and knowledge, the Camel-5b model is primed to offer unparalleled proficiency in understanding and executing language-based instructions.
One of the key differentiators of Camel-5b lies in its ability to process complex instructions and generate accurate, contextually appropriate responses. This makes it an ideal choice for a wide range of applications, including virtual assistants, customer support, content generation, and more. Additionally, the model's comprehensive training enables it to adapt and perform well under varying conditions and contexts, further expanding its potential use cases.
Live Demo
Live demo => https://chatcamel.vercel.app/
Deploying Camel
We used the Baseten platform to package and serve Camel-5B at scale. Utilizing the open source Truss model packaging framework, users can create a customized environment using the simple instructions found on GitHub. This repo allows users to maintain full control over the inference and deployment paths to meet their specific requirements. We would like to thank the Baseten team for their contributions in deploying and hosting the model.
Usage :
import torch from transformers import AutoTokenizer, AutoModelForCausalLM model_name = "Writer/camel-5b-hf" tokenizer = AutoTokenizer.from_pretrained(model_name) model = AutoModelForCausalLM.from_pretrained( model_name, device_map="auto", torch_dtype=torch.float16 ) instruction = "Describe a futuristic device that revolutionizes space travel." PROMPT_DICT = { "prompt_input": ( "Below is an instruction that describes a task, paired with an input that provides further context. " "Write a response that appropriately completes the request\n\n" "### Instruction:\n{instruction}\n\n### Input:\n{input}\n\n### Response:" ), "prompt_no_input": ( "Below is an instruction that describes a task. " "Write a response that appropriately completes the request.\n\n" "### Instruction:\n{instruction}\n\n### Response:" ), } text = ( PROMPT_DICT["prompt_no_input"].format(instruction=instruction) if not input else PROMPT_DICT["prompt_input"].format(instruction=instruction, input=input) ) model_inputs = tokenizer(text, return_tensors="pt").to("cuda") output_ids = model.generate( **model_inputs, max_length=256, ) output_text = tokenizer.batch_decode(output_ids, skip_special_tokens=True)[0] clean_output = output_text.split("### Response:")[1].strip() print(clean_output)
Limitations and Biases
Camel's core functionality is to take a string of text and predict the next token. While language models are widely used for other tasks, there are many unknowns in this work. When prompting Camel, keep in mind that the next statistically likely token is not always the token that produces the most "accurate" text. Never rely on Camel to produce factually correct results.
Camel was trained on Writer’s custom data. As with all language models, it is difficult to predict how Camel will respond to specific prompts, and offensive content may appear unexpectedly. We recommend that the outputs be curated or filtered by humans before they are released, both to censor undesirable content and to improve the quality of the results.
Camel VS. Llama
The Camel is essentially the Swiss Army knife of the animal kingdom - it can store water in its humps, survive extreme temperatures, and even provide a cushy ride for weary travelers. The llama, on the other hand, is basically just a glorified lawnmower with an attitude problem. Sure, they might have a cute, fuzzy face, but don't be deceived - one false move and you'll be greeted with a spit shower. The true MVP of the desert, and let the llama keep on spitting its way into obscurity.
Citation and Related Information
To cite this model:
@misc{Camel, author = {Writer Engineering team}, title = {{Camel-5B InstructGPT}}, howpublished = {\url{https://dev.writer.com}}, year = 2023, month = April }
||| |
https://huggingface.co/Writer/palmyra-20b-chat | Edit model card
Writer/palmyra-20b-chat
Usage
import torch from transformers import AutoTokenizer, AutoModelForCausalLM, TextStreamer model_name = "Writer/palmyra-20b-chat" tokenizer = AutoTokenizer.from_pretrained(model_name) model = AutoModelForCausalLM.from_pretrained( model_name, torch_dtype=torch.float16, device_map="auto", ) prompt = "What is the meaning of life?" input_text = ( "A chat between a curious user and an artificial intelligence assistant. " "The assistant gives helpful, detailed, and polite answers to the user's questions. " "USER: {prompt} " "ASSISTANT:" ) model_inputs = tokenizer(input_text.format(prompt=prompt), return_tensors="pt").to( "cuda" ) gen_conf = { "top_k": 20, "max_new_tokens": 2048, "temperature": 0.6, "do_sample": True, "eos_token_id": tokenizer.eos_token_id, } streamer = TextStreamer(tokenizer) if "token_type_ids" in model_inputs: del model_inputs["token_type_ids"] all_inputs = {**model_inputs, **gen_conf} output = model.generate(**all_inputs, streamer=streamer) print("-"*20) print(output)
Datasets used to train Writer/palmyra-20b-chat |
https://huggingface.co/w-brock | 1
Brock Imel
w-brock
w-brock
Research interests
None yet
Organizations
models
None public yet
datasets
None public yet |
https://huggingface.co/melisa | 2 1
Aneta Melisa Stal
melisa
Research interests
NLP
Organizations
models 2
melisa/taco-decoder
Updated Jul 1, 2022
melisa/taco-tagger
Updated Jun 29, 2022
datasets
None public yet |
https://huggingface.co/manhal | 1
Manhal Daaboul
manhal
Research interests
None yet
Organizations
models
None public yet
datasets
None public yet |
https://huggingface.co/wassemgtk | 11 7 1
Waseem Al
wassemgtk
waseem_s
wassemgtk
Research interests
None yet
Organizations
Papers 1
arxiv:2307.03692
models 1
wassemgtk/snippetv2
Updated Jun 19, 2021
datasets
None public yet |
https://huggingface.co/datasets/Writer/Palmyra-instract-30 | You need to agree to share your contact information to access this dataset
This repository is publicly accessible, but you have to accept the conditions to access its files and content.
Log in or Sign Up to review the conditions and access this dataset content.
No dataset card yet
New: Create and edit this dataset card directly on the website!
Contribute a Dataset Card |
https://huggingface.co/writer-jr | 1
jr robinson
writer-jr
https://writer.com
writer-jr
Research interests
grammar and style ai
Organizations
models
None public yet
datasets
None public yet |
https://huggingface.co/djwo | 1 1
Doris Jwo
djwo
Research interests
None yet
Organizations
models
None public yet
datasets
None public yet |
https://huggingface.co/kiranr | 8 31 2
Kiran Kamble
kiranr
ki6an
Research interests
nlp,llm
Organizations
Papers 1
arxiv:2307.03692
models 1
kiranr/gpt2-tokenizer
Updated Jun 20
datasets
None public yet |
https://huggingface.co/muayad | 2
Muayad Sayed Ali
muayad
Research interests
None yet
Organizations
models
None public yet
datasets
None public yet |
https://huggingface.co/parikshithkulkarni | 1 1
Parikshith Kulkarni
parikshithkulkarni
Research interests
None yet
Organizations
Papers 1
arxiv:2307.03692
models
None public yet
datasets
None public yet |
https://huggingface.co/yakivy | 1
Yakiv Yereskovskyi
yakivy
Research interests
None yet
Organizations
models
None public yet
datasets
None public yet |