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Document common config attributes #11070

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Apr 5, 2021
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Document common config attributes #11070

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25 changes: 18 additions & 7 deletions src/transformers/configuration_utils.py
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Expand Up @@ -34,19 +34,30 @@ class PretrainedConfig(object):
Base class for all configuration classes. Handles a few parameters common to all models' configurations as well as
methods for loading/downloading/saving configurations.

Note: A configuration file can be loaded and saved to disk. Loading the configuration file and using this file to
initialize a model does **not** load the model weights. It only affects the model's configuration.
Note:
A configuration file can be loaded and saved to disk. Loading the configuration file and using this file to
initialize a model does **not** load the model weights. It only affects the model's configuration.
Comment on lines +37 to +39
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This is the proper syntax to render the note as a note.


Class attributes (overridden by derived classes)

- **model_type** (:obj:`str`): An identifier for the model type, serialized into the JSON file, and used to
- **model_type** (:obj:`str`) -- An identifier for the model type, serialized into the JSON file, and used to
recreate the correct object in :class:`~transformers.AutoConfig`.
- **is_composition** (:obj:`bool`): Whether the config class is composed of multiple sub-configs. In this case
the config has to be initialized from two or more configs of type :class:`~transformers.PretrainedConfig`
like: :class:`~transformers.EncoderDecoderConfig` or :class:`~RagConfig`.
- **keys_to_ignore_at_inference** (:obj:`List[str]`): A list of keys to ignore by default when looking at
- **is_composition** (:obj:`bool`) -- Whether the config class is composed of multiple sub-configs. In this
case the config has to be initialized from two or more configs of type
:class:`~transformers.PretrainedConfig` like: :class:`~transformers.EncoderDecoderConfig` or
:class:`~RagConfig`.
- **keys_to_ignore_at_inference** (:obj:`List[str]`) -- A list of keys to ignore by default when looking at
dictionary outputs of the model during inference.

Common attributes (present in all subclasses)

- **vocab_size** (:obj:`int`) -- The number of tokens in the vocabulary, which is also the first dimension of
the embeddings matrix (this attribute may be missing for models that don't have a text modality like ViT).
- **hidden_size** (:obj:`int`) -- The hidden size of the model.
- **num_attention_heads** (:obj:`int`) -- The number of attention heads used in the multi-head attention layers
of the model.
- **num_hidden_layers** (:obj:`int`) -- The number of blocks in the model.

Args:
name_or_path (:obj:`str`, `optional`, defaults to :obj:`""`):
Store the string that was passed to :func:`~transformers.PreTrainedModel.from_pretrained` or
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