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Documentation: RemBERT fixes #17641

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merged 3 commits into from Jun 15, 2022
Merged

Documentation: RemBERT fixes #17641

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ee4dca6
rembert: fix python codeblock
stefan-it Jun 9, 2022
ce718f0
rembert: use correct google/rembert checkpoint name in documentation
stefan-it Jun 9, 2022
d5abe2f
rembert: use correct google/rembert checkpoint name in TF documentation
stefan-it Jun 9, 2022
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17 changes: 9 additions & 8 deletions src/transformers/models/rembert/configuration_rembert.py
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Expand Up @@ -21,7 +21,7 @@
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
}

Expand Down Expand Up @@ -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__(
Expand Down
12 changes: 6 additions & 6 deletions src/transformers/models/rembert/modeling_rembert.py
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Expand Up @@ -786,7 +786,7 @@ class PreTrainedModel
@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,
)
Expand Down Expand Up @@ -939,7 +939,7 @@ def set_output_embeddings(self, new_embeddings):
@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,
)
Expand Down Expand Up @@ -1184,7 +1184,7 @@ def __init__(self, config):
@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,
)
Expand Down Expand Up @@ -1281,7 +1281,7 @@ def __init__(self, config):
@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,
)
Expand Down Expand Up @@ -1374,7 +1374,7 @@ def __init__(self, config):
@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,
)
Expand Down Expand Up @@ -1453,7 +1453,7 @@ def __init__(self, config):
@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,
)
Expand Down
14 changes: 7 additions & 7 deletions src/transformers/models/rembert/modeling_tf_rembert.py
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Expand Up @@ -938,7 +938,7 @@ def __init__(self, config: RemBertConfig, *inputs, **kwargs):
@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,
)
Expand Down Expand Up @@ -1041,7 +1041,7 @@ def get_lm_head(self) -> tf.keras.layers.Layer:
@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,
)
Expand Down Expand Up @@ -1131,7 +1131,7 @@ def prepare_inputs_for_generation(self, input_ids, past=None, attention_mask=Non
@unpack_inputs
@add_code_sample_docstrings(
processor_class=_TOKENIZER_FOR_DOC,
checkpoint="rembert",
checkpoint="google/rembert",
output_type=TFCausalLMOutputWithCrossAttentions,
config_class=_CONFIG_FOR_DOC,
)
Expand Down Expand Up @@ -1262,7 +1262,7 @@ def __init__(self, config: RemBertConfig, *inputs, **kwargs):
@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,
)
Expand Down Expand Up @@ -1352,7 +1352,7 @@ def dummy_inputs(self) -> Dict[str, tf.Tensor]:
@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,
)
Expand Down Expand Up @@ -1471,7 +1471,7 @@ def __init__(self, config: RemBertConfig, *inputs, **kwargs):
@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,
)
Expand Down Expand Up @@ -1550,7 +1550,7 @@ def __init__(self, config: RemBertConfig, *inputs, **kwargs):
@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,
)
Expand Down