Update doc examples feature extractor -> image processor (#20501)

* Update doc example feature extractor -> image processor

* Apply suggestions from code review
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amyeroberts
2022-11-30 14:50:55 +00:00
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@@ -53,11 +53,11 @@ Tips:
Techniques like data augmentation, optimization, and regularization were used in order to simulate training on a much larger dataset
(while only using ImageNet-1k for pre-training). The 5 variants available are (all trained on images of size 224x224):
*facebook/levit-128S*, *facebook/levit-128*, *facebook/levit-192*, *facebook/levit-256* and
*facebook/levit-384*. Note that one should use [`LevitFeatureExtractor`] in order to
*facebook/levit-384*. Note that one should use [`LevitImageProcessor`] in order to
prepare images for the model.
- [`LevitForImageClassificationWithTeacher`] currently supports only inference and not training or fine-tuning.
- 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)
(you can just replace [`ViTFeatureExtractor`] by [`LevitFeatureExtractor`] and [`ViTForImageClassification`] by [`LevitForImageClassification`] or [`LevitForImageClassificationWithTeacher`]).
(you can just replace [`ViTFeatureExtractor`] by [`LevitImageProcessor`] and [`ViTForImageClassification`] by [`LevitForImageClassification`] or [`LevitForImageClassificationWithTeacher`]).
This model was contributed by [anugunj](https://huggingface.co/anugunj). The original code can be found [here](https://github.com/facebookresearch/LeViT).