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thomwolf
2019-07-16 13:56:47 +02:00
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Pretrained models
================================================
Here is the full list of the currently provided pretrained models together with a short presentation of each model.
+===============+============================================================+===========================+
| Architecture | Shortcut name | Details of the model |
+===============+============================================================+===========================+
| | ``bert-base-uncased`` | 12-layer, 768-hidden, 12-heads, 110M parameters
| | | Trained on lower-cased English text |
| +------------------------------------------------------------+---------------------------+
| | ``bert-large-uncased`` | 24-layer, 1024-hidden, 16-heads, 340M parameters
| | | Trained on lower-cased English text |
| +------------------------------------------------------------+---------------------------+
| | ``bert-base-cased`` | 12-layer, 768-hidden, 12-heads, 110M parameters
| | | Trained on cased English text |
| +------------------------------------------------------------+---------------------------+
| | ``bert-large-cased`` | 24-layer, 1024-hidden, 16-heads, 340M parameters |
| | | Trained on cased English text |
| +------------------------------------------------------------+---------------------------+
| | ``bert-base-multilingual-uncased`` | (Original, not recommended) 12-layer, 768-hidden, 12-heads, 110M parameters
| | | Trained on lower-cased text in the top 102 languages with the largest Wikipedias
| | | (see `details <https://github.com/google-research/bert/blob/master/multilingual.md>`_) |
| +------------------------------------------------------------+---------------------------+
| | ``bert-base-multilingual-cased`` | (New, **recommended**) 12-layer, 768-hidden, 12-heads, 110M parameters |
| | | Trained on cased text in the top 104 languages with the largest Wikipedias
| | | (see `details <https://github.com/google-research/bert/blob/master/multilingual.md>`_) |
| +------------------------------------------------------------+---------------------------+
| BERT | ``bert-base-chinese`` | 12-layer, 768-hidden, 12-heads, 110M parameters |
| | | Trained on cased 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, 340M 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, 340M 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, 340M parameters |
| | | The ``bert-large-uncased-whole-word-masking`` model fine-tuned on SQuAD |
| | | (see details of fine-tuning in the `example section`_) |
| +------------------------------------------------------------+---------------------------+
| | ``bert-large-cased-whole-word-masking-finetuned-squad`` | 24-layer, 1024-hidden, 16-heads, 340M parameters |
| | | The ``bert-large-cased-whole-word-masking`` model fine-tuned on SQuAD |
| | | (see `details of fine-tuning in the example section <https://huggingface.co/pytorch-transformers/examples.html>`_) |
| +------------------------------------------------------------+---------------------------+
| | ``bert-base-cased-finetuned-mrpc`` | 12-layer, 768-hidden, 12-heads, 110M parameters |
| | | The ``bert-base-cased`` model fine-tuned on MRPC |
| | | (see `details of fine-tuning in the example section <https://huggingface.co/pytorch-transformers/examples.html>`_) |
+---------------+------------------------------------------------------------+---------------------------+
| GPT | Cells may span columns. |
+---------------+----------------------------------------------------------------------------------------+
.. <https://huggingface.co/pytorch-transformers/examples.html>`_