Add CamemBERT to auto files and docs

docs/source/pretrained_models.rst

@@ -155,5 +155,9 @@ Here is the full list of the currently provided pretrained models together with
 | 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>`__)                                                 |
++-------------------+------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
 
-.. <https://huggingface.co/transformers/examples.html>`__
+.. <https://huggingface.co/transformers/examples.html>`__
\ No newline at end of file

transformers/configuration_auto.py

@@ -27,6 +27,7 @@ from .configuration_xlm import XLMConfig
 from .configuration_roberta import RobertaConfig
 from .configuration_distilbert import DistilBertConfig
 from .configuration_ctrl import CTRLConfig
+from .configuration_camembert import CamembertConfig
 
 logger = logging.getLogger(__name__)
 
@@ -50,6 +51,7 @@ class AutoConfig(object):
             - contains `xlnet`: XLNetConfig (XLNet model)
             - contains `xlm`: XLMConfig (XLM model)
             - contains `roberta`: RobertaConfig (RoBERTa model)
+            - contains `camembert`: CamembertConfig (CamemBERT model)
             - contains `ctrl` : CTRLConfig (CTRL model)
         This class cannot be instantiated using `__init__()` (throw an error).
     """
@@ -72,6 +74,7 @@ class AutoConfig(object):
             - contains `xlnet`: XLNetConfig (XLNet model)
             - contains `xlm`: XLMConfig (XLM model)
             - contains `roberta`: RobertaConfig (RoBERTa model)
+            - contains `camembert`: CamembertConfig (CamemBERT model)
             - contains `ctrl` : CTRLConfig (CTRL model)
         Params:
             pretrained_model_name_or_path: either:
@@ -116,6 +119,8 @@ class AutoConfig(object):
         """
         if 'distilbert' in pretrained_model_name_or_path:
             return DistilBertConfig.from_pretrained(pretrained_model_name_or_path, **kwargs)
+        elif 'camembert' in pretrained_model_name_or_path:
+            return CamembertConfig.from_pretrained(pretrained_model_name_or_path, **kwargs)
         elif 'roberta' in pretrained_model_name_or_path:
             return RobertaConfig.from_pretrained(pretrained_model_name_or_path, **kwargs)
         elif 'bert' in pretrained_model_name_or_path:
@@ -134,4 +139,4 @@ class AutoConfig(object):
             return CTRLConfig.from_pretrained(pretrained_model_name_or_path, **kwargs)
         raise ValueError("Unrecognized model identifier in {}. Should contains one of "
                          "'bert', 'openai-gpt', 'gpt2', 'transfo-xl', 'xlnet', "
-                         "'xlm', 'roberta', 'ctrl'".format(pretrained_model_name_or_path))
+                         "'xlm', 'roberta', 'camembert', 'ctrl'".format(pretrained_model_name_or_path))

transformers/tokenization_auto.py

@@ -27,6 +27,7 @@ from .tokenization_xlnet import XLNetTokenizer
 from .tokenization_xlm import XLMTokenizer
 from .tokenization_roberta import RobertaTokenizer
 from .tokenization_distilbert import DistilBertTokenizer
+from .tokenization_camembert import CamembertTokenizer
 
 logger = logging.getLogger(__name__)
 
@@ -41,6 +42,7 @@ class AutoTokenizer(object):
 
         The tokenizer class to instantiate is selected as the first pattern matching
         in the `pretrained_model_name_or_path` string (in the following order):
+            - contains `camembert`: CamembertTokenizer (CamemBERT model)
             - contains `distilbert`: DistilBertTokenizer (DistilBert model)
             - contains `roberta`: RobertaTokenizer (RoBERTa model)
             - contains `bert`: BertTokenizer (Bert model)
@@ -64,8 +66,9 @@ class AutoTokenizer(object):
 
         The tokenizer class to instantiate is selected as the first pattern matching
         in the `pretrained_model_name_or_path` string (in the following order):
+            - contains `camembert`: CamembertTokenizer (CamemBERT model)
             - contains `distilbert`: DistilBertTokenizer (DistilBert model)
-            - contains `roberta`: RobertaTokenizer (XLM model)
+            - contains `roberta`: RobertaTokenizer (RoBERTa model)
             - contains `bert`: BertTokenizer (Bert model)
             - contains `openai-gpt`: OpenAIGPTTokenizer (OpenAI GPT model)
             - contains `gpt2`: GPT2Tokenizer (OpenAI GPT-2 model)
@@ -103,6 +106,8 @@ class AutoTokenizer(object):
         """
         if 'distilbert' in pretrained_model_name_or_path:
             return DistilBertTokenizer.from_pretrained(pretrained_model_name_or_path, *inputs, **kwargs)
+        elif 'camembert' in pretrained_model_name_or_path:
+            return CamembertTokenizer.from_pretrained(pretrained_model_name_or_path, *inputs, **kwargs)
         elif 'roberta' in pretrained_model_name_or_path:
             return RobertaTokenizer.from_pretrained(pretrained_model_name_or_path, *inputs, **kwargs)
         elif 'bert' in pretrained_model_name_or_path:
@@ -121,4 +126,4 @@ class AutoTokenizer(object):
             return CTRLTokenizer.from_pretrained(pretrained_model_name_or_path, *inputs, **kwargs)
         raise ValueError("Unrecognized model identifier in {}. Should contains one of "
                          "'bert', 'openai-gpt', 'gpt2', 'transfo-xl', 'xlnet', "
-                         "'xlm', 'roberta', 'ctrl'".format(pretrained_model_name_or_path))
+                         "'xlm', 'roberta', 'camembert', 'ctrl'".format(pretrained_model_name_or_path))