Update doc examples feature extractor -> image processor (#20501)
* Update doc example feature extractor -> image processor * Apply suggestions from code review
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@@ -53,11 +53,11 @@ Tips:
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Techniques like data augmentation, optimization, and regularization were used in order to simulate training on a much larger dataset
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(while only using ImageNet-1k for pre-training). The 5 variants available are (all trained on images of size 224x224):
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*facebook/levit-128S*, *facebook/levit-128*, *facebook/levit-192*, *facebook/levit-256* and
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*facebook/levit-384*. Note that one should use [`LevitFeatureExtractor`] in order to
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*facebook/levit-384*. Note that one should use [`LevitImageProcessor`] in order to
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prepare images for the model.
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- [`LevitForImageClassificationWithTeacher`] currently supports only inference and not training or fine-tuning.
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- You can check out demo notebooks regarding inference as well as fine-tuning on custom data [here](https://github.com/NielsRogge/Transformers-Tutorials/tree/master/VisionTransformer)
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(you can just replace [`ViTFeatureExtractor`] by [`LevitFeatureExtractor`] and [`ViTForImageClassification`] by [`LevitForImageClassification`] or [`LevitForImageClassificationWithTeacher`]).
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(you can just replace [`ViTFeatureExtractor`] by [`LevitImageProcessor`] and [`ViTForImageClassification`] by [`LevitForImageClassification`] or [`LevitForImageClassificationWithTeacher`]).
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This model was contributed by [anugunj](https://huggingface.co/anugunj). The original code can be found [here](https://github.com/facebookresearch/LeViT).
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