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Add CamemBERT to auto files and docs

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Louis MARTIN
2019-11-12 17:41:41 -08:00
committed by Julien Chaumond
parent 694d4fcbb6
commit 035fea5315
3 changed files with 18 additions and 4 deletions
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4
docs/source/pretrained_models.rst
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@@ -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 | | CTRL | ``ctrl`` | | 48-layer, 1280-hidden, 16-heads, 1.6B parameters |
| | | | Salesforce's Large-sized CTRL English model | | | | | 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>`__

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

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