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* 1,100%! * Clean * Don't touch DS * Experiment with dtype allocation * skip test_load_save_without_tied_weights test * A little faster * Include proper upscaling? * Fixup tests * Potentially skip? * Let's see if this fixes git history * Maintain new dtype * Fin * Rm hook idea for now * New approach, see what breaks * stage * Clean * Stash * Should be fin now, just need to mark failing models * Clean up * Simplify * Deal with weird models * Enc/Dec * Skip w/ reason * Adjust test * Fix test * one more test * Keep experimenting * Fix ref * TO REMOVE: testing feedback CI * Right push * Update tests/utils/test_modeling_utils.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * disable * Add new func * Test nits from Amy * Update src/transformers/modeling_utils.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Adjust comment * Adjust comment on skip * make private * Fin * Should be a not flag * Clarify and rename test --------- Co-authored-by: Marc Sun <marc@huggingface.co> Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
74 lines
2.4 KiB
Markdown
74 lines
2.4 KiB
Markdown
<!--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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⚠️ Note that this file is in Markdown but contain specific syntax for our doc-builder (similar to MDX) that may not be
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rendered properly in your Markdown viewer.
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-->
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# Models
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The base classes [`PreTrainedModel`], [`TFPreTrainedModel`], and
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[`FlaxPreTrainedModel`] implement the common methods for loading/saving a model either from a local
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file or directory, or from a pretrained model configuration provided by the library (downloaded from HuggingFace's AWS
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S3 repository).
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[`PreTrainedModel`] and [`TFPreTrainedModel`] also implement a few methods which
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are common among all the models to:
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- resize the input token embeddings when new tokens are added to the vocabulary
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- prune the attention heads of the model.
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The other methods that are common to each model are defined in [`~modeling_utils.ModuleUtilsMixin`]
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(for the PyTorch models) and [`~modeling_tf_utils.TFModuleUtilsMixin`] (for the TensorFlow models) or
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for text generation, [`~generation.GenerationMixin`] (for the PyTorch models),
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[`~generation.TFGenerationMixin`] (for the TensorFlow models) and
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[`~generation.FlaxGenerationMixin`] (for the Flax/JAX models).
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## PreTrainedModel
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[[autodoc]] PreTrainedModel
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- push_to_hub
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- all
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Custom models should also include a `_supports_assign_param_buffer`, which determines if superfast init can apply
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on the particular model. Signs that your model needs this are if `test_save_and_load_from_pretrained` fails. If so,
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set this to `False`.
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## ModuleUtilsMixin
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[[autodoc]] modeling_utils.ModuleUtilsMixin
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## TFPreTrainedModel
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[[autodoc]] TFPreTrainedModel
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- push_to_hub
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- all
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## TFModelUtilsMixin
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[[autodoc]] modeling_tf_utils.TFModelUtilsMixin
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## FlaxPreTrainedModel
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[[autodoc]] FlaxPreTrainedModel
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- push_to_hub
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- all
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## Pushing to the Hub
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[[autodoc]] utils.PushToHubMixin
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## Sharded checkpoints
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[[autodoc]] modeling_utils.load_sharded_checkpoint
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