Stanfordnlp
Rank:Average Model Cost: $0.0000
Number of Runs: 20,960
Models by this creator
stanza-he
stanza-he
The Stanza-he model is a pre-trained model for token classification, specifically for the Hebrew language. It can be used to label and classify individual tokens in a text, such as identifying named entities, part-of-speech tags, or any other relevant labels. This model has been trained on a large corpus of Hebrew text and can be utilized to perform various natural language processing tasks in Hebrew.
$-/run
7.6K
Huggingface
stanza-en
$-/run
4.6K
Huggingface
backpack-gpt2
backpack-gpt2
Model Card for Backpack-GPT2 The Backpack-GPT2 language model is an instance of the Backpack architecture, intended to combine strong modeling performance with an interface for interpretability and control. Most details about this model and its training should be accessed in the paper, Backpack Language Models. See also backpackmodels.science. Table of Contents Model Card for Backpack-GPT2 Table of Contents Model Details Model Description Uses Bias, Risks, and Limitations Training Details Training Data Training Procedure Environmental Impact Technical Specifications [optional] Model Architecture and Objective Compute Infrastructure Hardware Software Citation Model Card Authors [optional] Model Card Contact How to Get Started with the Model Model Details Model Description The Backpack-GPT2 is a Backpack-based language model, an architecture intended to combine strong modeling performance with an interface for interpretability and control. Developed by: John Hewitt, John Thickstun, Christopher D. Manning, Percy Liang Shared by [Optional]: More information needed Model type: Language model Language(s) (NLP): en License: apache-2.0 Resources for more information: GitHub Repo Associated Paper Uses This model is intended for use in the study and development of increasingly interpretable methods in natural language processing. It is not directly fit for any production use. Bias, Risks, and Limitations Significant research has explored bias and fairness issues with language models (see, e.g., Sheng et al. (2021) and Bender et al. (2021)). Predictions generated by the model may include disturbing and harmful stereotypes across protected classes; identity characteristics; and sensitive, social, and occupational groups. This model in particular is limited in its capabilities, and with a brand new architecture, less is known about its biases than, e.g., Transformer-based models. Training Details Training Data This model was trained on the OpenWebText corpus. Training Procedure This model was trained for 100k gradient steps with a batch size of 512k tokens and a linearly decaying learning rate from 6e-4 to zero, with a linear warmup of 5k steps. Environmental Impact Hardware Type: 4 A100 GPUs (40G) Hours used: Roughly 4 days. Cloud Provider: Stanford compute. Compute Region: Stanford energy grid. Model Architecture and Objective This model was trained to minimize the cross-entropy loss, and is a Backpack language model. Compute Infrastructure This model was trained on a slurm cluster. Hardware This model was trained on 4 A100s. Software This model was trained with FlashAttention and PyTorch Citation BibTeX: Model Card Authors [optional] John Hewitt Model Card Contact johnhew@cs.stanford.edu How to Get Started with the Model
$-/run
2.0K
Huggingface
stanza-es
stanza-es
Stanza model for Spanish (es) Stanza is a collection of accurate and efficient tools for the linguistic analysis of many human languages. Starting from raw text to syntactic analysis and entity recognition, Stanza brings state-of-the-art NLP models to languages of your choosing. Find more about it in our website and our GitHub repository. This card and repo were automatically prepared with hugging_stanza.py in the stanfordnlp/huggingface-models repo Last updated 2023-06-10 06:33:53.984
$-/run
1.4K
Huggingface
stanza-de
$-/run
1.4K
Huggingface
stanza-nl
$-/run
1.3K
Huggingface
SteamSHP-flan-t5-xl
$-/run
835
Huggingface
stanza-zh-hans
stanza-zh-hans
Stanza model for Simplified_Chinese (zh-hans) Stanza is a collection of accurate and efficient tools for the linguistic analysis of many human languages. Starting from raw text to syntactic analysis and entity recognition, Stanza brings state-of-the-art NLP models to languages of your choosing. Find more about it in our website and our GitHub repository. This card and repo were automatically prepared with hugging_stanza.py in the stanfordnlp/huggingface-models repo Last updated 2023-05-19 04:37:57.698
$-/run
790
Huggingface
stanza-ar
$-/run
565
Huggingface
stanza-ko
stanza-ko
Stanza model for Korean (ko) Stanza is a collection of accurate and efficient tools for the linguistic analysis of many human languages. Starting from raw text to syntactic analysis and entity recognition, Stanza brings state-of-the-art NLP models to languages of your choosing. Find more about it in our website and our GitHub repository. This card and repo were automatically prepared with hugging_stanza.py in the stanfordnlp/huggingface-models repo Last updated 2023-05-19 04:06:35.694
$-/run
551
Huggingface