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c8be8a9adb
* refactor GPT Config to allow dyn. properties * make attribute_map a class attribute * remove old code * update unit test to test config: Add test for common properties setter * update unit test to test config: Add test for common properties passed as parameters to __init__ * update to black code format * Allow that setters are not defined for certain config classes * update config classes to implement attribute_map * bugfix lxmert config - id2labels was not defined when num_labels was set * update broken configs - add attribute_maps * update bart config * update black codestyle * update documentation on common config attributes * update GPTJ config to new attribute map * update docs on common attributes * gptj config: add max_position_embeddings * gptj config: format with black * update speech to text 2 config * format doc file to max_len 119 * update config template
32 lines
1.5 KiB
ReStructuredText
32 lines
1.5 KiB
ReStructuredText
..
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Copyright 2020 The HuggingFace Team. All rights reserved.
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Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
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the License. You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
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an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the
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specific language governing permissions and limitations under the License.
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Configuration
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-----------------------------------------------------------------------------------------------------------------------
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The base class :class:`~transformers.PretrainedConfig` implements the common methods for loading/saving a configuration
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either from a local file or directory, or from a pretrained model configuration provided by the library (downloaded
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from HuggingFace's AWS S3 repository).
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Each derived config class implements model specific attributes. Common attributes present in all config classes are:
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:obj:`hidden_size`, :obj:`num_attention_heads`, and :obj:`num_hidden_layers`. Text models further implement:
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:obj:`vocab_size`.
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PretrainedConfig
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.PretrainedConfig
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:special-members: push_to_hub
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:members:
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