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Kill model archive maps (#4636)

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* Kill model archive maps

* Fixup

* Also kill model_archive_map for MaskedBertPreTrainedModel

* Unhook config_archive_map

* Tokenizers: align with model id changes

* make style && make quality

* Fix CI
This commit is contained in:
Julien Chaumond
2020-06-02 09:39:33 -04:00
committed by GitHub
parent 47a551d17b
commit d4c2cb402d
115 changed files with 792 additions and 1323 deletions
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34
docs/source/pretrained_models.rst
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@@ -63,33 +63,33 @@ For a list that includes community-uploaded models, refer to `https://huggingfac
| | | | Trained on uncased German text by DBMDZ |
| | | (see `details on dbmdz repository <https://github.com/dbmdz/german-bert>`__). |
| +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
| | ``bert-base-japanese`` | | 12-layer, 768-hidden, 12-heads, 110M parameters. |
| | ``cl-tohoku/bert-base-japanese`` | | 12-layer, 768-hidden, 12-heads, 110M parameters. |
| | | | Trained on Japanese text. Text is tokenized with MeCab and WordPiece. |
| | | | `MeCab <https://taku910.github.io/mecab/>`__ is required for tokenization. |
| | | (see `details on cl-tohoku repository <https://github.com/cl-tohoku/bert-japanese>`__). |
| +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
| | ``bert-base-japanese-whole-word-masking`` | | 12-layer, 768-hidden, 12-heads, 110M parameters. |
| | ``cl-tohoku/bert-base-japanese-whole-word-masking`` | | 12-layer, 768-hidden, 12-heads, 110M parameters. |
| | | | Trained on Japanese text using Whole-Word-Masking. Text is tokenized with MeCab and WordPiece. |
| | | | `MeCab <https://taku910.github.io/mecab/>`__ is required for tokenization. |
| | | (see `details on cl-tohoku repository <https://github.com/cl-tohoku/bert-japanese>`__). |
| +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
| | ``bert-base-japanese-char`` | | 12-layer, 768-hidden, 12-heads, 110M parameters. |
| | ``cl-tohoku/bert-base-japanese-char`` | | 12-layer, 768-hidden, 12-heads, 110M parameters. |
| | | | Trained on Japanese text. Text is tokenized into characters. |
| | | (see `details on cl-tohoku repository <https://github.com/cl-tohoku/bert-japanese>`__). |
| +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
| | ``bert-base-japanese-char-whole-word-masking`` | | 12-layer, 768-hidden, 12-heads, 110M parameters. |
| | ``cl-tohoku/bert-base-japanese-char-whole-word-masking`` | | 12-layer, 768-hidden, 12-heads, 110M 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>`__). |
| +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
| | ``bert-base-finnish-cased-v1`` | | 12-layer, 768-hidden, 12-heads, 110M parameters. |
| | ``TurkuNLP/bert-base-finnish-cased-v1`` | | 12-layer, 768-hidden, 12-heads, 110M parameters. |
| | | | Trained on cased Finnish text. |
| | | (see `details on turkunlp.org <http://turkunlp.org/FinBERT/>`__). |
| +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
| | ``bert-base-finnish-uncased-v1`` | | 12-layer, 768-hidden, 12-heads, 110M parameters. |
| | ``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/>`__). |
| +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
| | ``bert-base-dutch-cased`` | | 12-layer, 768-hidden, 12-heads, 110M parameters. |
| | ``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/>`__). |
+-------------------+------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
@@ -259,32 +259,32 @@ For a list that includes community-uploaded models, refer to `https://huggingfac
| | ``xlm-roberta-large`` | | ~355M parameters with 24-layers, 1027-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-small-cased`` | | 6-layer, 512-hidden, 8-heads, 54M parameters |
| FlauBERT | ``flaubert/flaubert_small_cased`` | | 6-layer, 512-hidden, 8-heads, 54M parameters |
| | | | FlauBERT small architecture |
| | | (see `details <https://github.com/getalp/Flaubert>`__) |
| +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
| | ``flaubert-base-uncased`` | | 12-layer, 768-hidden, 12-heads, 137M parameters |
| | ``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-base-cased`` | | 12-layer, 768-hidden, 12-heads, 138M parameters |
| | ``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-large-cased`` | | 24-layer, 1024-hidden, 16-heads, 373M parameters |
| | ``flaubert/flaubert_large_cased`` | | 24-layer, 1024-hidden, 16-heads, 373M parameters |
| | | | FlauBERT large architecture |
| | | (see `details <https://github.com/getalp/Flaubert>`__) |
+-------------------+------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
| Bart | ``bart-large`` | | 24-layer, 1024-hidden, 16-heads, 406M parameters |
| Bart | ``facebook/bart-large`` | | 24-layer, 1024-hidden, 16-heads, 406M parameters |
| | | (see `details <https://github.com/pytorch/fairseq/tree/master/examples/bart>`_) |
| +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
| | ``bart-large-mnli`` | | Adds a 2 layer classification head with 1 million 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 |
| +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
| | ``bart-large-cnn`` | | 12-layer, 1024-hidden, 16-heads, 406M parameters (same as base) |
| | ``facebook/bart-large-cnn`` | | 12-layer, 1024-hidden, 16-heads, 406M parameters (same as base) |
| | | | bart-large base architecture finetuned on cnn summarization task |
| +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
| | ``mbart-large-en-ro`` | | 12-layer, 1024-hidden, 16-heads, 880M parameters |
| | ``facebook/mbart-large-en-ro`` | | 12-layer, 1024-hidden, 16-heads, 880M parameters |
| | | | bart-large architecture pretrained on cc25 multilingual data , finetuned on WMT english romanian translation. |
+-------------------+------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
| DialoGPT | ``DialoGPT-small`` | | 12-layer, 768-hidden, 12-heads, 124M parameters |
@@ -305,9 +305,9 @@ For a list that includes community-uploaded models, refer to `https://huggingfac
| 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>`_) |
+-------------------+------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
| Longformer | ``longformer-base-4096`` | | 12-layer, 768-hidden, 12-heads, ~149M parameters |
| 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 |
| +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
| | ``longformer-large-4096`` | | 24-layer, 1024-hidden, 16-heads, ~435M parameters |
| | ``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 |
+-------------------+------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+