pretrained_models.rst

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    Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
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Pretrained models
=======================================================================================================================

Here is a partial list of some of the available pretrained models together with a short presentation of each model.

For the full list, refer to `https://huggingface.co/models <https://huggingface.co/models>`__.

+--------------------+------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
| Architecture       | Model id                                                   | Details of the model                                                                                                                  |
+====================+============================================================+=======================================================================================================================================+
| 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, 336M parameters.                                                                                   |
|                    |                                                            | | Trained on lower-cased English text.                                                                                                |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``bert-base-cased``                                        | | 12-layer, 768-hidden, 12-heads, 109M parameters.                                                                                    |
|                    |                                                            | | Trained on cased English text.                                                                                                      |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``bert-large-cased``                                       | | 24-layer, 1024-hidden, 16-heads, 335M parameters.                                                                                   |
|                    |                                                            | | Trained on cased English text.                                                                                                      |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``bert-base-multilingual-uncased``                         | | (Original, not recommended) 12-layer, 768-hidden, 12-heads, 168M 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, 179M 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, 103M 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>`__).                                                             |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``bert-large-uncased-whole-word-masking``                  | | 24-layer, 1024-hidden, 16-heads, 336M parameters.                                                                                   |
|                    |                                                            | | Trained on lower-cased English text using Whole-Word-Masking                                                                        |
|                    |                                                            |                                                                                                                                       |
|                    |                                                            | (see `details <https://github.com/google-research/bert/#bert>`__).                                                                    |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``bert-large-cased-whole-word-masking``                    | | 24-layer, 1024-hidden, 16-heads, 335M parameters.                                                                                   |
|                    |                                                            | | Trained on cased English text using Whole-Word-Masking                                                                              |
|                    |                                                            |                                                                                                                                       |
|                    |                                                            | (see `details <https://github.com/google-research/bert/#bert>`__).                                                                    |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``bert-large-uncased-whole-word-masking-finetuned-squad``  | | 24-layer, 1024-hidden, 16-heads, 336M parameters.                                                                                   |
|                    |                                                            | | 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/transformers/tree/master/examples>`__).           |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``bert-large-cased-whole-word-masking-finetuned-squad``    | | 24-layer, 1024-hidden, 16-heads, 335M 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/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/transformers/examples.html>`__)                           |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``bert-base-german-dbmdz-cased``                           | | 12-layer, 768-hidden, 12-heads, 110M parameters.                                                                                    |
|                    |                                                            | | Trained on cased German text by DBMDZ                                                                                               |
|                    |                                                            |                                                                                                                                       |
|                    |                                                            | (see `details on dbmdz repository <https://github.com/dbmdz/german-bert>`__).                                                         |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``bert-base-german-dbmdz-uncased``                         | | 12-layer, 768-hidden, 12-heads, 110M parameters.                                                                                    |
|                    |                                                            | | Trained on uncased German text by DBMDZ                                                                                             |
|                    |                                                            |                                                                                                                                       |
|                    |                                                            | (see `details on dbmdz repository <https://github.com/dbmdz/german-bert>`__).                                                         |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``cl-tohoku/bert-base-japanese``                           | | 12-layer, 768-hidden, 12-heads, 111M parameters.                                                                                    |
|                    |                                                            | | Trained on Japanese text. Text is tokenized with MeCab and WordPiece and this requires some extra dependencies,                     |
|                    |                                                            | | `fugashi <https://github.com/polm/fugashi>`__ which is a wrapper around `MeCab <https://taku910.github.io/mecab/>`__.               |
|                    |                                                            | | Use ``pip install transformers["ja"]`` (or ``pip install -e .["ja"]`` if you install from source) to install them.                  |
|                    |                                                            |                                                                                                                                       |
|                    |                                                            | (see `details on cl-tohoku repository <https://github.com/cl-tohoku/bert-japanese>`__).                                               |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``cl-tohoku/bert-base-japanese-whole-word-masking``        | | 12-layer, 768-hidden, 12-heads, 111M parameters.                                                                                    |
|                    |                                                            | | Trained on Japanese text. Text is tokenized with MeCab and WordPiece and this requires some extra dependencies,                     |
|                    |                                                            | | `fugashi <https://github.com/polm/fugashi>`__ which is a wrapper around `MeCab <https://taku910.github.io/mecab/>`__.               |
|                    |                                                            | | Use ``pip install transformers["ja"]`` (or ``pip install -e .["ja"]`` if you install from source) to install them.                  |
|                    |                                                            |                                                                                                                                       |
|                    |                                                            | (see `details on cl-tohoku repository <https://github.com/cl-tohoku/bert-japanese>`__).                                               |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``cl-tohoku/bert-base-japanese-char``                      | | 12-layer, 768-hidden, 12-heads, 90M parameters.                                                                                     |
|                    |                                                            | | Trained on Japanese text. Text is tokenized into characters.                                                                        |
|                    |                                                            |                                                                                                                                       |
|                    |                                                            | (see `details on cl-tohoku repository <https://github.com/cl-tohoku/bert-japanese>`__).                                               |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``cl-tohoku/bert-base-japanese-char-whole-word-masking``   | | 12-layer, 768-hidden, 12-heads, 90M parameters.                                                                                     |
|                    |                                                            | | Trained on Japanese text using Whole-Word-Masking. Text is tokenized into characters.                                               |
|                    |                                                            |                                                                                                                                       |
|                    |                                                            | (see `details on cl-tohoku repository <https://github.com/cl-tohoku/bert-japanese>`__).                                               |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``TurkuNLP/bert-base-finnish-cased-v1``                    | | 12-layer, 768-hidden, 12-heads, 125M parameters.                                                                                    |
|                    |                                                            | | Trained on cased Finnish text.                                                                                                      |
|                    |                                                            |                                                                                                                                       |
|                    |                                                            | (see `details on turkunlp.org <http://turkunlp.org/FinBERT/>`__).                                                                     |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``TurkuNLP/bert-base-finnish-uncased-v1``                  | | 12-layer, 768-hidden, 12-heads, 110M parameters.                                                                                    |
|                    |                                                            | | Trained on uncased Finnish text.                                                                                                    |
|                    |                                                            |                                                                                                                                       |
|                    |                                                            | (see `details on turkunlp.org <http://turkunlp.org/FinBERT/>`__).                                                                     |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``wietsedv/bert-base-dutch-cased``                         | | 12-layer, 768-hidden, 12-heads, 110M parameters.                                                                                    |
|                    |                                                            | | Trained on cased Dutch text.                                                                                                        |
|                    |                                                            |                                                                                                                                       |
|                    |                                                            | (see `details on wietsedv repository <https://github.com/wietsedv/bertje/>`__).                                                       |
+--------------------+------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
| 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                                                                                           |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``gpt2-large``                                             | | 36-layer, 1280-hidden, 20-heads, 774M parameters.                                                                                   |
|                    |                                                            | | OpenAI's Large-sized GPT-2 English model                                                                                            |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``gpt2-xl``                                                | | 48-layer, 1600-hidden, 25-heads, 1558M parameters.                                                                                  |
|                    |                                                            | | OpenAI's XL-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, 2048-hidden, 16-heads                                                                                                     |
|                    |                                                            | | XLM English model                                                                                                                   |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``xlm-mlm-ende-1024``                                      | | 6-layer, 1024-hidden, 8-heads                                                                                                       |
|                    |                                                            | | XLM English-German model trained on the concatenation of English and German wikipedia                                               |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``xlm-mlm-enfr-1024``                                      | | 6-layer, 1024-hidden, 8-heads                                                                                                       |
|                    |                                                            | | XLM English-French model trained on the concatenation of English and French wikipedia                                               |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``xlm-mlm-enro-1024``                                      | | 6-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``                                      | | 6-layer, 1024-hidden, 8-heads                                                                                                       |
|                    |                                                            | | XLM English-French model trained with CLM (Causal Language Modeling) on the concatenation of English and French wikipedia           |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``xlm-clm-ende-1024``                                      | | 6-layer, 1024-hidden, 8-heads                                                                                                       |
|                    |                                                            | | XLM English-German model trained with CLM (Causal Language Modeling) on the concatenation of English and German wikipedia           |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``xlm-mlm-17-1280``                                        | | 16-layer, 1280-hidden, 16-heads                                                                                                     |
|                    |                                                            | | XLM model trained with MLM (Masked Language Modeling) on 17 languages.                                                              |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``xlm-mlm-100-1280``                                       | | 16-layer, 1280-hidden, 16-heads                                                                                                     |
|                    |                                                            | | XLM model trained with MLM (Masked Language Modeling) on 100 languages.                                                             |
+--------------------+------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
| RoBERTa            | ``roberta-base``                                           | | 12-layer, 768-hidden, 12-heads, 125M parameters                                                                                     |
|                    |                                                            | | RoBERTa using the BERT-base architecture                                                                                            |
|                    |                                                            |                                                                                                                                       |
|                    |                                                            | (see `details <https://github.com/pytorch/fairseq/tree/master/examples/roberta>`__)                                                   |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``roberta-large``                                          | | 24-layer, 1024-hidden, 16-heads, 355M parameters                                                                                    |
|                    |                                                            | | RoBERTa using the BERT-large architecture                                                                                           |
|                    |                                                            |                                                                                                                                       |
|                    |                                                            | (see `details <https://github.com/pytorch/fairseq/tree/master/examples/roberta>`__)                                                   |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``roberta-large-mnli``                                     | | 24-layer, 1024-hidden, 16-heads, 355M parameters                                                                                    |
|                    |                                                            | | ``roberta-large`` fine-tuned on `MNLI <http://www.nyu.edu/projects/bowman/multinli/>`__.                                            |
|                    |                                                            |                                                                                                                                       |
|                    |                                                            | (see `details <https://github.com/pytorch/fairseq/tree/master/examples/roberta>`__)                                                   |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``distilroberta-base``                                     | | 6-layer, 768-hidden, 12-heads, 82M parameters                                                                                       |
|                    |                                                            | | The DistilRoBERTa model distilled from the RoBERTa model `roberta-base` checkpoint.                                                 |
|                    |                                                            |                                                                                                                                       |
|                    |                                                            | (see `details <https://github.com/huggingface/transformers/tree/master/examples/distillation>`__)                                     |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``roberta-base-openai-detector``                           | | 12-layer, 768-hidden, 12-heads, 125M parameters                                                                                     |
|                    |                                                            | | ``roberta-base`` fine-tuned by OpenAI on the outputs of the 1.5B-parameter GPT-2 model.                                             |
|                    |                                                            |                                                                                                                                       |
|                    |                                                            | (see `details <https://github.com/openai/gpt-2-output-dataset/tree/master/detector>`__)                                               |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``roberta-large-openai-detector``                          | | 24-layer, 1024-hidden, 16-heads, 355M parameters                                                                                    |
|                    |                                                            | | ``roberta-large`` fine-tuned by OpenAI on the outputs of the 1.5B-parameter GPT-2 model.                                            |
|                    |                                                            |                                                                                                                                       |
|                    |                                                            | (see `details <https://github.com/openai/gpt-2-output-dataset/tree/master/detector>`__)                                               |
+--------------------+------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
| DistilBERT         | ``distilbert-base-uncased``                                | | 6-layer, 768-hidden, 12-heads, 66M parameters                                                                                       |
|                    |                                                            | | The DistilBERT model distilled from the BERT model `bert-base-uncased` checkpoint                                                   |
|                    |                                                            |                                                                                                                                       |
|                    |                                                            | (see `details <https://github.com/huggingface/transformers/tree/master/examples/distillation>`__)                                     |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``distilbert-base-uncased-distilled-squad``                | | 6-layer, 768-hidden, 12-heads, 66M parameters                                                                                       |
|                    |                                                            | | The DistilBERT model distilled from the BERT model `bert-base-uncased` checkpoint, with an additional linear layer.                 |
|                    |                                                            |                                                                                                                                       |
|                    |                                                            | (see `details <https://github.com/huggingface/transformers/tree/master/examples/distillation>`__)                                     |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``distilbert-base-cased``                                  | | 6-layer, 768-hidden, 12-heads, 65M parameters                                                                                       |
|                    |                                                            | | The DistilBERT model distilled from the BERT model `bert-base-cased` checkpoint                                                     |
|                    |                                                            |                                                                                                                                       |
|                    |                                                            | (see `details <https://github.com/huggingface/transformers/tree/master/examples/distillation>`__)                                     |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``distilbert-base-cased-distilled-squad``                  | | 6-layer, 768-hidden, 12-heads, 65M parameters                                                                                       |
|                    |                                                            | | The DistilBERT model distilled from the BERT model `bert-base-cased` checkpoint, with an additional question answering layer.       |
|                    |                                                            |                                                                                                                                       |
|                    |                                                            | (see `details <https://github.com/huggingface/transformers/tree/master/examples/distillation>`__)                                     |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``distilgpt2``                                             | | 6-layer, 768-hidden, 12-heads, 82M parameters                                                                                       |
|                    |                                                            | | The DistilGPT2 model distilled from the GPT2 model `gpt2` checkpoint.                                                               |
|                    |                                                            |                                                                                                                                       |
|                    |                                                            | (see `details <https://github.com/huggingface/transformers/tree/master/examples/distillation>`__)                                     |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``distilbert-base-german-cased``                           | | 6-layer, 768-hidden, 12-heads, 66M parameters                                                                                       |
|                    |                                                            | | The German DistilBERT model distilled from the German DBMDZ BERT model `bert-base-german-dbmdz-cased` checkpoint.                   |
|                    |                                                            |                                                                                                                                       |
|                    |                                                            | (see `details <https://github.com/huggingface/transformers/tree/master/examples/distillation>`__)                                     |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``distilbert-base-multilingual-cased``                     | | 6-layer, 768-hidden, 12-heads, 134M parameters                                                                                      |
|                    |                                                            | | The multilingual DistilBERT model distilled from the Multilingual BERT model `bert-base-multilingual-cased` checkpoint.             |
|                    |                                                            |                                                                                                                                       |
|                    |                                                            | (see `details <https://github.com/huggingface/transformers/tree/master/examples/distillation>`__)                                     |
+--------------------+------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
| CTRL               | ``ctrl``                                                   | | 48-layer, 1280-hidden, 16-heads, 1.6B parameters                                                                                    |
|                    |                                                            | | Salesforce's Large-sized CTRL English model                                                                                         |
+--------------------+------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
| CamemBERT          | ``camembert-base``                                         | | 12-layer, 768-hidden, 12-heads, 110M parameters                                                                                     |
|                    |                                                            | | CamemBERT using the BERT-base architecture                                                                                          |
|                    |                                                            |                                                                                                                                       |
|                    |                                                            | (see `details <https://github.com/pytorch/fairseq/tree/master/examples/camembert>`__)                                                 |
+--------------------+------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
| ALBERT             | ``albert-base-v1``                                         | | 12 repeating layers, 128 embedding, 768-hidden, 12-heads, 11M parameters                                                            |
|                    |                                                            | | ALBERT base model                                                                                                                   |
|                    |                                                            |                                                                                                                                       |
|                    |                                                            | (see `details <https://github.com/google-research/ALBERT>`__)                                                                         |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``albert-large-v1``                                        | | 24 repeating layers, 128 embedding, 1024-hidden, 16-heads, 17M parameters                                                           |
|                    |                                                            | | ALBERT large model                                                                                                                  |
|                    |                                                            |                                                                                                                                       |
|                    |                                                            | (see `details <https://github.com/google-research/ALBERT>`__)                                                                         |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``albert-xlarge-v1``                                       | | 24 repeating layers, 128 embedding, 2048-hidden, 16-heads, 58M parameters                                                           |
|                    |                                                            | | ALBERT xlarge model                                                                                                                 |
|                    |                                                            |                                                                                                                                       |
|                    |                                                            | (see `details <https://github.com/google-research/ALBERT>`__)                                                                         |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``albert-xxlarge-v1``                                      | | 12 repeating layer, 128 embedding, 4096-hidden, 64-heads, 223M parameters                                                           |
|                    |                                                            | | ALBERT xxlarge model                                                                                                                |
|                    |                                                            |                                                                                                                                       |
|                    |                                                            | (see `details <https://github.com/google-research/ALBERT>`__)                                                                         |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``albert-base-v2``                                         | | 12 repeating layers, 128 embedding, 768-hidden, 12-heads, 11M parameters                                                            |
|                    |                                                            | | ALBERT base model with no dropout, additional training data and longer training                                                     |
|                    |                                                            |                                                                                                                                       |
|                    |                                                            | (see `details <https://github.com/google-research/ALBERT>`__)                                                                         |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``albert-large-v2``                                        | | 24 repeating layers, 128 embedding, 1024-hidden, 16-heads, 17M parameters                                                           |
|                    |                                                            | | ALBERT large model with no dropout, additional training data and longer training                                                    |
|                    |                                                            |                                                                                                                                       |
|                    |                                                            | (see `details <https://github.com/google-research/ALBERT>`__)                                                                         |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``albert-xlarge-v2``                                       | | 24 repeating layers, 128 embedding, 2048-hidden, 16-heads, 58M parameters                                                           |
|                    |                                                            | | ALBERT xlarge model with no dropout, additional training data and longer training                                                   |
|                    |                                                            |                                                                                                                                       |
|                    |                                                            | (see `details <https://github.com/google-research/ALBERT>`__)                                                                         |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``albert-xxlarge-v2``                                      | | 12 repeating layer, 128 embedding, 4096-hidden, 64-heads, 223M parameters                                                           |
|                    |                                                            | | ALBERT xxlarge model with no dropout, additional training data and longer training                                                  |
|                    |                                                            |                                                                                                                                       |
|                    |                                                            | (see `details <https://github.com/google-research/ALBERT>`__)                                                                         |
+--------------------+------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
| T5                 | ``t5-small``                                               | | ~60M parameters with 6-layers, 512-hidden-state, 2048 feed-forward hidden-state, 8-heads,                                           |
|                    |                                                            | | Trained on English text: the Colossal Clean Crawled Corpus (C4)                                                                     |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``t5-base``                                                | | ~220M parameters with 12-layers, 768-hidden-state, 3072 feed-forward hidden-state, 12-heads,                                        |
|                    |                                                            | | Trained on English text: the Colossal Clean Crawled Corpus (C4)                                                                     |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``t5-large``                                               | | ~770M parameters with 24-layers, 1024-hidden-state, 4096 feed-forward hidden-state, 16-heads,                                       |
|                    |                                                            | | Trained on English text: the Colossal Clean Crawled Corpus (C4)                                                                     |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``t5-3B``                                                  | | ~2.8B parameters with 24-layers, 1024-hidden-state, 16384 feed-forward hidden-state, 32-heads,                                      |
|                    |                                                            | | Trained on English text: the Colossal Clean Crawled Corpus (C4)                                                                     |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``t5-11B``                                                 | | ~11B parameters with 24-layers, 1024-hidden-state, 65536 feed-forward hidden-state, 128-heads,                                      |
|                    |                                                            | | Trained on English text: the Colossal Clean Crawled Corpus (C4)                                                                     |
+--------------------+------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
| XLM-RoBERTa        | ``xlm-roberta-base``                                       | | ~270M parameters with 12-layers, 768-hidden-state, 3072 feed-forward hidden-state, 8-heads,                                         |
|                    |                                                            | | Trained on on 2.5 TB of newly created clean CommonCrawl data in 100 languages                                                       |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``xlm-roberta-large``                                      | | ~550M parameters with 24-layers, 1024-hidden-state, 4096 feed-forward hidden-state, 16-heads,                                       |
|                    |                                                            | | Trained on 2.5 TB of newly created clean CommonCrawl data in 100 languages                                                          |
+--------------------+------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
| FlauBERT           | ``flaubert/flaubert_small_cased``                          | | 6-layer, 512-hidden, 8-heads, 54M parameters                                                                                        |
|                    |                                                            | | FlauBERT small architecture                                                                                                         |
|                    |                                                            |                                                                                                                                       |
|                    |                                                            | (see `details <https://github.com/getalp/Flaubert>`__)                                                                                |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``flaubert/flaubert_base_uncased``                         | | 12-layer, 768-hidden, 12-heads, 137M parameters                                                                                     |
|                    |                                                            | | FlauBERT base architecture with uncased vocabulary                                                                                  |
|                    |                                                            |                                                                                                                                       |
|                    |                                                            | (see `details <https://github.com/getalp/Flaubert>`__)                                                                                |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``flaubert/flaubert_base_cased``                           | | 12-layer, 768-hidden, 12-heads, 138M parameters                                                                                     |
|                    |                                                            | | FlauBERT base architecture with cased vocabulary                                                                                    |
|                    |                                                            |                                                                                                                                       |
|                    |                                                            | (see `details <https://github.com/getalp/Flaubert>`__)                                                                                |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``flaubert/flaubert_large_cased``                          | | 24-layer, 1024-hidden, 16-heads, 373M parameters                                                                                    |
|                    |                                                            | | FlauBERT large architecture                                                                                                         |
|                    |                                                            |                                                                                                                                       |
|                    |                                                            | (see `details <https://github.com/getalp/Flaubert>`__)                                                                                |
+--------------------+------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
| Bart               | ``facebook/bart-large``                                    | | 24-layer, 1024-hidden, 16-heads, 406M parameters                                                                                    |
|                    |                                                            |                                                                                                                                       |
|                    |                                                            | (see `details <https://github.com/pytorch/fairseq/tree/master/examples/bart>`_)                                                       |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``facebook/bart-base``                                     | | 12-layer, 768-hidden, 16-heads, 139M parameters                                                                                     |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``facebook/bart-large-mnli``                               | | Adds a 2 layer classification head with 1 million parameters                                                                        |
|                    |                                                            | | bart-large base architecture with a classification head, finetuned on MNLI                                                          |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``facebook/bart-large-cnn``                                | | 24-layer, 1024-hidden, 16-heads, 406M parameters       (same as large)                                                              |
|                    |                                                            | | bart-large base architecture finetuned on cnn summarization task                                                                    |
+--------------------+------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
| BARThez            | ``moussaKam/barthez``                                      | | 12-layer,  768-hidden, 12-heads, 216M parameters                                                                                    |
|                    |                                                            |                                                                                                                                       |
|                    |                                                            | (see `details <https://github.com/moussaKam/BARThez>`__)                                                                              |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``moussaKam/mbarthez``                                     | | 24-layer, 1024-hidden, 16-heads, 561M parameters                                                                                    |
+--------------------+------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
| DialoGPT           | ``DialoGPT-small``                                         | | 12-layer, 768-hidden, 12-heads, 124M parameters                                                                                     |
|                    |                                                            | | Trained on English text: 147M conversation-like exchanges extracted from Reddit.                                                    |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``DialoGPT-medium``                                        | | 24-layer, 1024-hidden, 16-heads, 355M parameters                                                                                    |
|                    |                                                            | | Trained on English text: 147M conversation-like exchanges extracted from Reddit.                                                    |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``DialoGPT-large``                                         | | 36-layer, 1280-hidden, 20-heads, 774M parameters                                                                                    |
|                    |                                                            | | Trained on English text: 147M conversation-like exchanges extracted from Reddit.                                                    |
+--------------------+------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
| Reformer           | ``reformer-enwik8``                                        | | 12-layer, 1024-hidden, 8-heads, 149M parameters                                                                                     |
|                    |                                                            | | Trained on English Wikipedia data - enwik8.                                                                                         |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``reformer-crime-and-punishment``                          | | 6-layer, 256-hidden, 2-heads, 3M parameters                                                                                         |
|                    |                                                            | | Trained on English text: Crime and Punishment novel by Fyodor Dostoyevsky.                                                          |
+--------------------+------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
| MarianMT           | ``Helsinki-NLP/opus-mt-{src}-{tgt}``                       | | 12-layer, 512-hidden, 8-heads, ~74M parameter Machine translation models. Parameter counts vary depending on vocab size.            |
|                    |                                                            | | (see `model list <https://huggingface.co/Helsinki-NLP>`_)                                                                           |
+--------------------+------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
| Pegasus            | ``google/pegasus-{dataset}``                               | | 16-layer, 1024-hidden, 16-heads, ~568M parameter, 2.2 GB for summary. `model list <https://huggingface.co/models?search=pegasus>`__ |
+--------------------+------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
| Longformer         | ``allenai/longformer-base-4096``                           | | 12-layer, 768-hidden, 12-heads, ~149M parameters                                                                                    |
|                    |                                                            | | Starting from RoBERTa-base checkpoint, trained on documents of max length 4,096                                                     |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``allenai/longformer-large-4096``                          | | 24-layer, 1024-hidden, 16-heads, ~435M parameters                                                                                   |
|                    |                                                            | | Starting from RoBERTa-large checkpoint, trained on documents of max length 4,096                                                    |
+--------------------+------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
| MBart              | ``facebook/mbart-large-cc25``                              | | 24-layer, 1024-hidden, 16-heads, 610M parameters                                                                                    |
|                    |                                                            | | mBART (bart-large architecture) model trained on 25 languages' monolingual corpus                                                   |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``facebook/mbart-large-en-ro``                             | | 24-layer, 1024-hidden, 16-heads, 610M parameters                                                                                    |
|                    |                                                            | | mbart-large-cc25 model finetuned on WMT english romanian translation.                                                               |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``facebook/mbart-large-50``                                | | 24-layer, 1024-hidden, 16-heads,                                                                                                    |
|                    |                                                            | | mBART model trained on 50 languages' monolingual corpus.                                                                            |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``facebook/mbart-large-50-one-to-many-mmt``                | | 24-layer, 1024-hidden, 16-heads,                                                                                                    |
|                    |                                                            | | mbart-50-large model finetuned for one (English) to many multilingual machine translation covering 50 languages.                    |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``facebook/mbart-large-50-many-to-many-mmt``               | | 24-layer, 1024-hidden, 16-heads,                                                                                                    |
|                    |                                                            | | mbart-50-large model finetuned for many to many multilingual machine translation covering 50 languages.                             |
+--------------------+------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
| Lxmert             | ``lxmert-base-uncased``                                    | | 9-language layers, 9-relationship layers, and 12-cross-modality layers                                                              |
|                    |                                                            | | 768-hidden, 12-heads (for each layer) ~ 228M parameters                                                                             |
|                    |                                                            | | Starting from lxmert-base checkpoint, trained on over 9 million image-text couplets from COCO, VisualGenome, GQA, VQA               |
+--------------------+------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
| Funnel Transformer | ``funnel-transformer/small``                               | | 14 layers: 3 blocks of 4 layers then 2 layers decoder, 768-hidden, 12-heads, 130M parameters                                        |
|                    |                                                            |                                                                                                                                       |
|                    |                                                            | (see `details <https://github.com/laiguokun/Funnel-Transformer>`__)                                                                   |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``funnel-transformer/small-base``                          | | 12 layers: 3 blocks of 4 layers (no decoder), 768-hidden, 12-heads, 115M parameters                                                 |
|                    |                                                            |                                                                                                                                       |
|                    |                                                            | (see `details <https://github.com/laiguokun/Funnel-Transformer>`__)                                                                   |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``funnel-transformer/medium``                              | | 14 layers: 3 blocks 6, 3x2, 3x2 layers then 2 layers decoder, 768-hidden, 12-heads, 130M parameters                                 |
|                    |                                                            |                                                                                                                                       |
|                    |                                                            | (see `details <https://github.com/laiguokun/Funnel-Transformer>`__)                                                                   |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``funnel-transformer/medium-base``                         | | 12 layers: 3 blocks 6, 3x2, 3x2 layers(no decoder), 768-hidden, 12-heads, 115M parameters                                           |
|                    |                                                            |                                                                                                                                       |
|                    |                                                            | (see `details <https://github.com/laiguokun/Funnel-Transformer>`__)                                                                   |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``funnel-transformer/intermediate``                        | | 20 layers: 3 blocks of 6 layers then 2 layers decoder, 768-hidden, 12-heads, 177M parameters                                        |
|                    |                                                            |                                                                                                                                       |
|                    |                                                            | (see `details <https://github.com/laiguokun/Funnel-Transformer>`__)                                                                   |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``funnel-transformer/intermediate-base``                   | | 18 layers: 3 blocks of 6 layers (no decoder), 768-hidden, 12-heads, 161M parameters                                                 |
|                    |                                                            |                                                                                                                                       |
|                    |                                                            | (see `details <https://github.com/laiguokun/Funnel-Transformer>`__)                                                                   |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``funnel-transformer/large``                               | | 26 layers: 3 blocks of 8 layers then 2 layers decoder, 1024-hidden, 12-heads, 386M parameters                                       |
|                    |                                                            |                                                                                                                                       |
|                    |                                                            | (see `details <https://github.com/laiguokun/Funnel-Transformer>`__)                                                                   |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``funnel-transformer/large-base``                          | | 24 layers: 3 blocks of 8 layers (no decoder), 1024-hidden, 12-heads, 358M parameters                                                |
|                    |                                                            |                                                                                                                                       |
|                    |                                                            | (see `details <https://github.com/laiguokun/Funnel-Transformer>`__)                                                                   |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``funnel-transformer/xlarge``                              | | 32 layers: 3 blocks of 10 layers then 2 layers decoder, 1024-hidden, 12-heads, 468M parameters                                      |
|                    |                                                            |                                                                                                                                       |
|                    |                                                            | (see `details <https://github.com/laiguokun/Funnel-Transformer>`__)                                                                   |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``funnel-transformer/xlarge-base``                         | | 30 layers: 3 blocks of 10 layers (no decoder), 1024-hidden, 12-heads, 440M parameters                                               |
|                    |                                                            |                                                                                                                                       |
|                    |                                                            | (see `details <https://github.com/laiguokun/Funnel-Transformer>`__)                                                                   |
+--------------------+------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
| LayoutLM           | ``microsoft/layoutlm-base-uncased``                        | | 12 layers, 768-hidden, 12-heads, 113M parameters                                                                                    |
|                    |                                                            |                                                                                                                                       |
|                    |                                                            | (see `details <https://github.com/microsoft/unilm/tree/master/layoutlm>`__)                                                           |
+                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``microsoft/layoutlm-large-uncased``                       | | 24 layers, 1024-hidden, 16-heads, 343M parameters                                                                                   |
|                    |                                                            |                                                                                                                                       |
|                    |                                                            | (see `details <https://github.com/microsoft/unilm/tree/master/layoutlm>`__)                                                           |
+--------------------+------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
| DeBERTa            | ``microsoft/deberta-base``                                 | | 12-layer, 768-hidden, 12-heads, ~125M parameters                                                                                    |
|                    |                                                            | | DeBERTa using the BERT-base architecture                                                                                            |
|                    |                                                            |                                                                                                                                       |
|                    |                                                            | (see `details <https://github.com/microsoft/DeBERTa>`__)                                                                              |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``microsoft/deberta-large``                                | | 24-layer, 1024-hidden, 16-heads, ~390M parameters                                                                                   |
|                    |                                                            | | DeBERTa using the BERT-large architecture                                                                                           |
|                    |                                                            |                                                                                                                                       |
|                    |                                                            | (see `details <https://github.com/microsoft/DeBERTa>`__)                                                                              |
+--------------------+------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
| SqueezeBERT        | ``squeezebert/squeezebert-uncased``                        | | 12-layer, 768-hidden, 12-heads, 51M parameters, 4.3x faster than bert-base-uncased on a smartphone.                                 |
|                    |                                                            | | SqueezeBERT architecture pretrained from scratch on masked language model (MLM) and sentence order prediction (SOP) tasks.          |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``squeezebert/squeezebert-mnli``                           | | 12-layer, 768-hidden, 12-heads, 51M parameters, 4.3x faster than bert-base-uncased on a smartphone.                                 |
|                    |                                                            | | This is the squeezebert-uncased model finetuned on MNLI sentence pair classification task with distillation from electra-base.      |
|                    +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
|                    | ``squeezebert/squeezebert-mnli-headless``                  | | 12-layer, 768-hidden, 12-heads, 51M parameters, 4.3x faster than bert-base-uncased on a smartphone.                                 |
|                    |                                                            | | This is the squeezebert-uncased model finetuned on MNLI sentence pair classification task with distillation from electra-base.      |
|                    |                                                            | | The final classification layer is removed, so when you finetune, the final layer will be reinitialized.                             |
+--------------------+------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+