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Change BloomConfig docstring #19336

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merged 4 commits into from Oct 5, 2022
Merged

Change BloomConfig docstring #19336

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d99d89f
change `BloomConfig` docstring
younesbelkada Oct 5, 2022
671ae11
Update src/transformers/models/bloom/configuration_bloom.py
younesbelkada Oct 5, 2022
b3478f0
Update src/transformers/models/bloom/configuration_bloom.py
younesbelkada Oct 5, 2022
137f156
make style
younesbelkada Oct 5, 2022
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14 changes: 8 additions & 6 deletions src/transformers/models/bloom/configuration_bloom.py
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Expand Up @@ -53,14 +53,16 @@ class BloomConfig(PretrainedConfig):


Args:
vocab_size (`int`, *optional*, defaults to 50257):
Vocabulary size of the Bloom model. Defines the number of different tokens that can be represented by the
`inputs_ids` passed when calling [`BloomModel`].
hidden_size (`int`, *optional*, defaults to 768):
vocab_size (`int`, *optional*, defaults to 250880):
Vocabulary size of the Bloom model. Defines the maximum number of different tokens that can be represented
by the `inputs_ids` passed when calling [`BloomModel`]. Check [this
discussion](https://huggingface.co/bigscience/bloom/discussions/120#633d28389addb8530b406c2a) on how the
`vocab_size` has been defined.
hidden_size (`int`, *optional*, defaults to 64):
Dimensionality of the embeddings and hidden states.
n_layer (`int`, *optional*, defaults to 12):
n_layer (`int`, *optional*, defaults to 2):
Number of hidden layers in the Transformer encoder.
n_head (`int`, *optional*, defaults to 12):
n_head (`int`, *optional*, defaults to 8):
Number of attention heads for each attention layer in the Transformer encoder.
layer_norm_epsilon (`float`, *optional*, defaults to 1e-5):
The epsilon to use in the layer normalization layers.
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