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298 lines
6.7 KiB
Markdown
298 lines
6.7 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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# Auto Classes
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In many cases, the architecture you want to use can be guessed from the name or the path of the pretrained model you
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are supplying to the `from_pretrained()` method. AutoClasses are here to do this job for you so that you
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automatically retrieve the relevant model given the name/path to the pretrained weights/config/vocabulary.
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Instantiating one of [`AutoConfig`], [`AutoModel`], and
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[`AutoTokenizer`] will directly create a class of the relevant architecture. For instance
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```python
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model = AutoModel.from_pretrained("google-bert/bert-base-cased", device_map="auto")
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```
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will create a model that is an instance of [`BertModel`].
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There is one class of `AutoModel` for each task.
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## Extending the Auto Classes
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Each of the auto classes has a method to be extended with your custom classes. For instance, if you have defined a
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custom class of model `NewModel`, make sure you have a `NewModelConfig` then you can add those to the auto
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classes like this:
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```python
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from transformers import AutoConfig, AutoModel
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AutoConfig.register("new-model", NewModelConfig)
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AutoModel.register(NewModelConfig, NewModel)
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```
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You will then be able to use the auto classes like you would usually do!
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<Tip warning={true}>
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If your `NewModelConfig` is a subclass of [`~transformers.PreTrainedConfig`], make sure its
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`model_type` attribute is set to the same key you use when registering the config (here `"new-model"`).
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Likewise, if your `NewModel` is a subclass of [`PreTrainedModel`], make sure its
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`config_class` attribute is set to the same class you use when registering the model (here
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`NewModelConfig`).
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</Tip>
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## AutoConfig
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[[autodoc]] AutoConfig
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## AutoTokenizer
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[[autodoc]] AutoTokenizer
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## AutoFeatureExtractor
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[[autodoc]] AutoFeatureExtractor
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## AutoImageProcessor
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[[autodoc]] AutoImageProcessor
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## AutoVideoProcessor
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[[autodoc]] AutoVideoProcessor
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## AutoProcessor
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[[autodoc]] AutoProcessor
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## Generic model classes
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The following auto classes are available for instantiating a base model class without a specific head.
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### AutoModel
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[[autodoc]] AutoModel
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## Generic pretraining classes
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The following auto classes are available for instantiating a model with a pretraining head.
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### AutoModelForPreTraining
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[[autodoc]] AutoModelForPreTraining
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## Natural Language Processing
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The following auto classes are available for the following natural language processing tasks.
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### AutoModelForCausalLM
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[[autodoc]] AutoModelForCausalLM
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### AutoModelForMaskedLM
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[[autodoc]] AutoModelForMaskedLM
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### AutoModelForMaskGeneration
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[[autodoc]] AutoModelForMaskGeneration
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### AutoModelForSeq2SeqLM
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[[autodoc]] AutoModelForSeq2SeqLM
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### AutoModelForSequenceClassification
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[[autodoc]] AutoModelForSequenceClassification
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### AutoModelForMultipleChoice
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[[autodoc]] AutoModelForMultipleChoice
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### AutoModelForNextSentencePrediction
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[[autodoc]] AutoModelForNextSentencePrediction
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### AutoModelForTokenClassification
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[[autodoc]] AutoModelForTokenClassification
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### AutoModelForQuestionAnswering
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[[autodoc]] AutoModelForQuestionAnswering
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### AutoModelForTextEncoding
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[[autodoc]] AutoModelForTextEncoding
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## Computer vision
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The following auto classes are available for the following computer vision tasks.
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### AutoModelForDepthEstimation
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[[autodoc]] AutoModelForDepthEstimation
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### AutoModelForNormalEstimation
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[[autodoc]] AutoModelForNormalEstimation
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### AutoModelForPointmapEstimation
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[[autodoc]] AutoModelForPointmapEstimation
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### AutoModelForImageMatting
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[[autodoc]] AutoModelForImageMatting
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### AutoModelForTextRecognition
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[[autodoc]] AutoModelForTextRecognition
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### AutoModelForTableRecognition
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[[autodoc]] AutoModelForTableRecognition
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### AutoModelForImageClassification
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[[autodoc]] AutoModelForImageClassification
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### AutoModelForVideoClassification
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[[autodoc]] AutoModelForVideoClassification
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### AutoModelForPoseEstimation
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[[autodoc]] AutoModelForPoseEstimation
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### AutoModelForKeypointDetection
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[[autodoc]] AutoModelForKeypointDetection
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### AutoModelForKeypointMatching
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[[autodoc]] AutoModelForKeypointMatching
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### AutoModelForMaskedImageModeling
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[[autodoc]] AutoModelForMaskedImageModeling
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### AutoModelForObjectDetection
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[[autodoc]] AutoModelForObjectDetection
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### AutoModelForImageSegmentation
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[[autodoc]] AutoModelForImageSegmentation
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### AutoModelForImageToImage
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[[autodoc]] AutoModelForImageToImage
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### AutoModelForSemanticSegmentation
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[[autodoc]] AutoModelForSemanticSegmentation
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### AutoModelForInstanceSegmentation
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[[autodoc]] AutoModelForInstanceSegmentation
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### AutoModelForUniversalSegmentation
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[[autodoc]] AutoModelForUniversalSegmentation
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### AutoModelForZeroShotImageClassification
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[[autodoc]] AutoModelForZeroShotImageClassification
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### AutoModelForZeroShotObjectDetection
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[[autodoc]] AutoModelForZeroShotObjectDetection
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## Audio
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The following auto classes are available for the following audio tasks.
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### AutoModelForAudioClassification
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[[autodoc]] AutoModelForAudioClassification
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### AutoModelForAudioFrameClassification
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[[autodoc]] AutoModelForAudioFrameClassification
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### AutoModelForCTC
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[[autodoc]] AutoModelForCTC
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### AutoModelForTDT
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[[autodoc]] AutoModelForTDT
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### AutoModelForSpeechSeq2Seq
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[[autodoc]] AutoModelForSpeechSeq2Seq
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### AutoModelForAudioXVector
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[[autodoc]] AutoModelForAudioXVector
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### AutoModelForTextToSpectrogram
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[[autodoc]] AutoModelForTextToSpectrogram
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### AutoModelForTextToWaveform
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[[autodoc]] AutoModelForTextToWaveform
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### AutoModelForAudioTokenization
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[[autodoc]] AutoModelForAudioTokenization
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## Multimodal
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The following auto classes are available for the following multimodal tasks.
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### AutoModelForMultimodalLM
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[[autodoc]] AutoModelForMultimodalLM
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### AutoModelForTableQuestionAnswering
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[[autodoc]] AutoModelForTableQuestionAnswering
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### AutoModelForDocumentQuestionAnswering
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[[autodoc]] AutoModelForDocumentQuestionAnswering
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### AutoModelForVisualQuestionAnswering
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[[autodoc]] AutoModelForVisualQuestionAnswering
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### AutoModelForImageTextToText
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[[autodoc]] AutoModelForImageTextToText
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## Time Series
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### AutoModelForTimeSeriesPrediction
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[[autodoc]] AutoModelForTimeSeriesPrediction
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