Skip to content

GitLab

Unverified Commit 6f05ad72 authored by Lysandre Debut's avatar Lysandre Debut Committed by GitHub
Browse files

Merge pull request #791 from huggingface/doc 

RestructuredText table for pretrained models.
parents 0e918707 9d381e7b
Show whitespace changes
Inline Side-by-side
Showing with 94 additions and 53 deletions
docs/source/pretrained_models.rst
View file @ 6f05ad72
......@@ -3,57 +3,98 @@ Pretrained models
Here is the full list of the currently provided pretrained models together with a short presentation of each model.
+===============+============================================================+===========================+
+-------------------+------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------+
| Architecture | Shortcut name | Details of the model |
+===============+============================================================+===========================+
| | ``bert-base-uncased`` | 12-layer, 768-hidden, 12-heads, 110M parameters
+===================+============================================================+===========================================================================================================================+
| BERT | ``bert-base-uncased`` | 12-layer, 768-hidden, 12-heads, 110M parameters |
| | | Trained on lower-cased English text |
| +------------------------------------------------------------+---------------------------+
| | ``bert-large-uncased`` | 24-layer, 1024-hidden, 16-heads, 340M parameters
| +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------+
| | ``bert-large-uncased`` | 24-layer, 1024-hidden, 16-heads, 340M parameters |
| | | Trained on lower-cased English text |
| +------------------------------------------------------------+---------------------------+
| | ``bert-base-cased`` | 12-layer, 768-hidden, 12-heads, 110M parameters
| +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------+
| | ``bert-base-cased`` | 12-layer, 768-hidden, 12-heads, 110M parameters |
| | | Trained on cased English text |
| +------------------------------------------------------------+---------------------------+
| +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------+
| | ``bert-large-cased`` | 24-layer, 1024-hidden, 16-heads, 340M parameters |
| | | Trained on cased English text |
| +------------------------------------------------------------+---------------------------+
| | ``bert-base-multilingual-uncased`` | (Original, not recommended) 12-layer, 768-hidden, 12-heads, 110M parameters
| | | Trained on lower-cased text in the top 102 languages with the largest Wikipedias
| | | (see `details <https://github.com/google-research/bert/blob/master/multilingual.md>`_) |
| +------------------------------------------------------------+---------------------------+
| +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------+
| | ``bert-base-multilingual-uncased`` | (Original, not recommended) 12-layer, 768-hidden, 12-heads, 110M parameters |
| | | Trained on lower-cased text in the top 102 languages with the largest Wikipedias |
| | | (see `details <https://github.com/google-research/bert/blob/master/multilingual.md>`__) |
| +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------+
| | ``bert-base-multilingual-cased`` | (New, **recommended**) 12-layer, 768-hidden, 12-heads, 110M parameters |
| | | Trained on cased text in the top 104 languages with the largest Wikipedias
| | | (see `details <https://github.com/google-research/bert/blob/master/multilingual.md>`_) |
| +------------------------------------------------------------+---------------------------+
| BERT | ``bert-base-chinese`` | 12-layer, 768-hidden, 12-heads, 110M parameters |
| | | Trained on cased text in the top 104 languages with the largest Wikipedias |
| | | (see `details <https://github.com/google-research/bert/blob/master/multilingual.md>`__) |
| +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------+
| | ``bert-base-chinese`` | 12-layer, 768-hidden, 12-heads, 110M parameters |
| | | Trained on cased Chinese Simplified and Traditional text |
| +------------------------------------------------------------+---------------------------+
| +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------+
| | ``bert-base-german-cased`` | 12-layer, 768-hidden, 12-heads, 110M parameters |
| | | Trained on cased German text by Deepset.ai |
| | | (see `details on deepset.ai website <https://deepset.ai/german-bert>`_) |
| +------------------------------------------------------------+---------------------------+
| | | (see `details on deepset.ai website <https://deepset.ai/german-bert>`__) |
| +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------+
| | ``bert-large-uncased-whole-word-masking`` | 24-layer, 1024-hidden, 16-heads, 340M parameters |
| | | Trained on lower-cased English text using Whole-Word-Masking |
| | | (see `details <https://github.com/google-research/bert/#bert>`_) |
| +------------------------------------------------------------+---------------------------+
| | | (see `details <https://github.com/google-research/bert/#bert>`__) |
| +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------+
| | ``bert-large-cased-whole-word-masking`` | 24-layer, 1024-hidden, 16-heads, 340M parameters |
| | | Trained on cased English text using Whole-Word-Masking |
| | | (see `details <https://github.com/google-research/bert/#bert>`_) |
| +------------------------------------------------------------+---------------------------+
| | | (see `details <https://github.com/google-research/bert/#bert>`__) |
| +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------+
| | ``bert-large-uncased-whole-word-masking-finetuned-squad`` | 24-layer, 1024-hidden, 16-heads, 340M parameters |
| | | The ``bert-large-uncased-whole-word-masking`` model fine-tuned on SQuAD |
| | | (see details of fine-tuning in the `example section`_) |
| +------------------------------------------------------------+---------------------------+
| | | The ``bert-large-uncased-whole-word-masking`` model fine-tuned on SQuAD (see details of fine-tuning in the |
| | | `example section <https://github.com/huggingface/pytorch-transformers/tree/master/examples>`__) |
| +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------+
| | ``bert-large-cased-whole-word-masking-finetuned-squad`` | 24-layer, 1024-hidden, 16-heads, 340M parameters |
| | | The ``bert-large-cased-whole-word-masking`` model fine-tuned on SQuAD |
| | | (see `details of fine-tuning in the example section <https://huggingface.co/pytorch-transformers/examples.html>`_) |
| +------------------------------------------------------------+---------------------------+
| | | (see `details of fine-tuning in the example section <https://huggingface.co/pytorch-transformers/examples.html>`__) |
| +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------+
| | ``bert-base-cased-finetuned-mrpc`` | 12-layer, 768-hidden, 12-heads, 110M parameters |
| | | The ``bert-base-cased`` model fine-tuned on MRPC |
| | | (see `details of fine-tuning in the example section <https://huggingface.co/pytorch-transformers/examples.html>`_) |
+---------------+------------------------------------------------------------+---------------------------+
| GPT | Cells may span columns. |
+---------------+----------------------------------------------------------------------------------------+
| | | (see `details of fine-tuning in the example section <https://huggingface.co/pytorch-transformers/examples.html>`__) |
+-------------------+------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------+
| GPT | ``openai-gpt`` | 12-layer, 768-hidden, 12-heads, 110M parameters |
| | | OpenAI GPT English model |
+-------------------+------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------+
| GPT-2 | ``gpt2`` | 12-layer, 768-hidden, 12-heads, 117M parameters |
| | | OpenAI GPT-2 English model |
| +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------+
| | ``gpt2-medium`` | 24-layer, 1024-hidden, 16-heads, 345M parameters |
| | | OpenAI's Medium-sized GPT-2 English model |
+-------------------+------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------+
| Transformer-XL | ``transfo-xl-wt103`` | 18-layer, 1024-hidden, 16-heads, 257M parameters |
| | | English model trained on wikitext-103 |
+-------------------+------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------+
| XLNet | ``xlnet-base-cased`` | 12-layer, 768-hidden, 12-heads, 110M parameters |
| | | XLNet English model |
| +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------+
| | ``xlnet-large-cased`` | 24-layer, 1024-hidden, 16-heads, 340M parameters |
| | | XLNet Large English model |
+-------------------+------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------+
| XLM | ``xlm-mlm-en-2048`` | 12-layer, 1024-hidden, 8-heads |
| | | XLM English model |
| +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------+
| | ``xlm-mlm-ende-1024`` | 12-layer, 1024-hidden, 8-heads |
| | | XLM English-German Multi-language model |
| +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------+
| | ``xlm-mlm-enfr-1024`` | 12-layer, 1024-hidden, 8-heads |
| | | XLM English-French Multi-language model |
| +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------+
| | ``xlm-mlm-enro-1024`` | 12-layer, 1024-hidden, 8-heads |
| | | XLM English-Romanian Multi-language model |
| +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------+
| | ``xlm-mlm-xnli15-1024`` | 12-layer, 1024-hidden, 8-heads |
| | | XLM Model pre-trained with MLM on the `15 XNLI languages <https://github.com/facebookresearch/XNLI>`__. |
| +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------+
| | ``xlm-mlm-tlm-xnli15-1024`` | 12-layer, 1024-hidden, 8-heads |
| | | XLM Model pre-trained with MLM + TLM on the `15 XNLI languages <https://github.com/facebookresearch/XNLI>`__. |
| +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------+
| | ``xlm-clm-enfr-1024`` | 12-layer, 1024-hidden, 8-heads |
| | | XLM English model trained with CLM (Causal Language Modeling) |
| +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------+
| | ``xlm-clm-ende-1024`` | 12-layer, 1024-hidden, 8-heads |
| | | XLM English-German Multi-language model trained with CLM (Causal Language Modeling) |
+-------------------+------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------+
.. <https://huggingface.co/pytorch-transformers/examples.html>`_
\ No newline at end of file
.. <https://huggingface.co/pytorch-transformers/examples.html>`__
\ No newline at end of file
Markdown is supported
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment