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

src/transformers/models/rembert/configuration_rembert.py

@@ -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

@@ -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

@@ -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,
     )