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Unverified Commit 242cc6e2 authored by Stefan Schweter's avatar Stefan Schweter Committed by GitHub
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Documentation: RemBERT fixes (#17641) 

* rembert: fix python codeblock

* rembert: use correct google/rembert checkpoint name in documentation

* rembert: use correct google/rembert checkpoint name in TF documentation
parent b76290f4
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Showing with 22 additions and 21 deletions
src/transformers/models/rembert/configuration_rembert.py
View file @ 242cc6e2
......@@ -21,7 +21,7 @@ from ...utils import logging
logger = logging.get_logger(__name__)
REMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP = {
"rembert": "https://huggingface.co/google/rembert/resolve/main/config.json",
"google/rembert": "https://huggingface.co/google/rembert/resolve/main/config.json",
# See all RemBERT models at https://huggingface.co/models?filter=rembert
}
......@@ -80,16 +80,17 @@ class RemBertConfig(PretrainedConfig):
Example:
```python
>>> from transformers import RemBertModel, RemBertConfig
```
>>> # Initializing a RemBERT rembert style configuration
>>> configuration = RemBertConfig()
>>> from transformers import RemBertModel, RemBertConfig >>> # Initializing a RemBERT rembert style
configuration >>> configuration = RemBertConfig()
>>> # Initializing a model from the rembert style configuration
>>> model = RemBertModel(configuration)
>>> # Initializing a model from the rembert style configuration >>> model = RemBertModel(configuration)
>>> # Accessing the model configuration >>> configuration = model.config
"""
>>> # Accessing the model configuration
>>> configuration = model.config
```"""
model_type = "rembert"
def __init__(
......
src/transformers/models/rembert/modeling_rembert.py
View file @ 242cc6e2
......@@ -786,7 +786,7 @@ class RemBertModel(RemBertPreTrainedModel):
@add_start_docstrings_to_model_forward(REMBERT_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
processor_class=_TOKENIZER_FOR_DOC,
checkpoint="rembert",
checkpoint="google/rembert",
output_type=BaseModelOutputWithPastAndCrossAttentions,
config_class=_CONFIG_FOR_DOC,
)
......@@ -939,7 +939,7 @@ class RemBertForMaskedLM(RemBertPreTrainedModel):
@add_start_docstrings_to_model_forward(REMBERT_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
processor_class=_TOKENIZER_FOR_DOC,
checkpoint="rembert",
checkpoint="google/rembert",
output_type=MaskedLMOutput,
config_class=_CONFIG_FOR_DOC,
)
......@@ -1184,7 +1184,7 @@ class RemBertForSequenceClassification(RemBertPreTrainedModel):
@add_start_docstrings_to_model_forward(REMBERT_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
processor_class=_TOKENIZER_FOR_DOC,
checkpoint="rembert",
checkpoint="google/rembert",
output_type=SequenceClassifierOutput,
config_class=_CONFIG_FOR_DOC,
)
......@@ -1281,7 +1281,7 @@ class RemBertForMultipleChoice(RemBertPreTrainedModel):
@add_start_docstrings_to_model_forward(REMBERT_INPUTS_DOCSTRING.format("batch_size, num_choices, sequence_length"))
@add_code_sample_docstrings(
processor_class=_TOKENIZER_FOR_DOC,
checkpoint="rembert",
checkpoint="google/rembert",
output_type=MultipleChoiceModelOutput,
config_class=_CONFIG_FOR_DOC,
)
......@@ -1374,7 +1374,7 @@ class RemBertForTokenClassification(RemBertPreTrainedModel):
@add_start_docstrings_to_model_forward(REMBERT_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
processor_class=_TOKENIZER_FOR_DOC,
checkpoint="rembert",
checkpoint="google/rembert",
output_type=TokenClassifierOutput,
config_class=_CONFIG_FOR_DOC,
)
......@@ -1453,7 +1453,7 @@ class RemBertForQuestionAnswering(RemBertPreTrainedModel):
@add_start_docstrings_to_model_forward(REMBERT_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
processor_class=_TOKENIZER_FOR_DOC,
checkpoint="rembert",
checkpoint="google/rembert",
output_type=QuestionAnsweringModelOutput,
config_class=_CONFIG_FOR_DOC,
)
......
src/transformers/models/rembert/modeling_tf_rembert.py
View file @ 242cc6e2
......@@ -938,7 +938,7 @@ class TFRemBertModel(TFRemBertPreTrainedModel):
@add_start_docstrings_to_model_forward(REMBERT_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
processor_class=_TOKENIZER_FOR_DOC,
checkpoint="rembert",
checkpoint="google/rembert",
output_type=TFBaseModelOutputWithPoolingAndCrossAttentions,
config_class=_CONFIG_FOR_DOC,
)
......@@ -1041,7 +1041,7 @@ class TFRemBertForMaskedLM(TFRemBertPreTrainedModel, TFMaskedLanguageModelingLos
@add_start_docstrings_to_model_forward(REMBERT_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
processor_class=_TOKENIZER_FOR_DOC,
checkpoint="rembert",
checkpoint="google/rembert",
output_type=TFMaskedLMOutput,
config_class=_CONFIG_FOR_DOC,
)
......@@ -1131,7 +1131,7 @@ class TFRemBertForCausalLM(TFRemBertPreTrainedModel, TFCausalLanguageModelingLos
@unpack_inputs
@add_code_sample_docstrings(
processor_class=_TOKENIZER_FOR_DOC,
checkpoint="rembert",
checkpoint="google/rembert",
output_type=TFCausalLMOutputWithCrossAttentions,
config_class=_CONFIG_FOR_DOC,
)
......@@ -1262,7 +1262,7 @@ class TFRemBertForSequenceClassification(TFRemBertPreTrainedModel, TFSequenceCla
@add_start_docstrings_to_model_forward(REMBERT_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
processor_class=_TOKENIZER_FOR_DOC,
checkpoint="rembert",
checkpoint="google/rembert",
output_type=TFSequenceClassifierOutput,
config_class=_CONFIG_FOR_DOC,
)
......@@ -1352,7 +1352,7 @@ class TFRemBertForMultipleChoice(TFRemBertPreTrainedModel, TFMultipleChoiceLoss)
@add_start_docstrings_to_model_forward(REMBERT_INPUTS_DOCSTRING.format("batch_size, num_choices, sequence_length"))
@add_code_sample_docstrings(
processor_class=_TOKENIZER_FOR_DOC,
checkpoint="rembert",
checkpoint="google/rembert",
output_type=TFMultipleChoiceModelOutput,
config_class=_CONFIG_FOR_DOC,
)
......@@ -1471,7 +1471,7 @@ class TFRemBertForTokenClassification(TFRemBertPreTrainedModel, TFTokenClassific
@add_start_docstrings_to_model_forward(REMBERT_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
processor_class=_TOKENIZER_FOR_DOC,
checkpoint="rembert",
checkpoint="google/rembert",
output_type=TFTokenClassifierOutput,
config_class=_CONFIG_FOR_DOC,
)
......@@ -1550,7 +1550,7 @@ class TFRemBertForQuestionAnswering(TFRemBertPreTrainedModel, TFQuestionAnswerin
@add_start_docstrings_to_model_forward(REMBERT_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
processor_class=_TOKENIZER_FOR_DOC,
checkpoint="rembert",
checkpoint="google/rembert",
output_type=TFQuestionAnsweringModelOutput,
config_class=_CONFIG_FOR_DOC,
)
......
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