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Update README.md

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  # LeViT
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- LeViT128S model pre-trained on ImageNet-1k at resolution 224x224. It was introduced in the paper [LeViT: a Vision Transformer in ConvNet's Clothing for Faster Inference
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  ](https://arxiv.org/abs/2104.01136) by Graham et al. and first released in [this repository](https://github.com/facebookresearch/LeViT).
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  Disclaimer: The team releasing LeViT did not write a model card for this model so this model card has been written by the Hugging Face team.
@@ -33,8 +33,8 @@ import requests
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  url = 'http://images.cocodataset.org/val2017/000000039769.jpg'
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  image = Image.open(requests.get(url, stream=True).raw)
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- feature_extractor = LevitFeatureExtractor.from_pretrained('anugunj/levit-256')
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- model = LevitForImageClassificationWithTeacher.from_pretrained('anugunj/levit-256')
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  inputs = feature_extractor(images=image, return_tensors="pt")
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  outputs = model(**inputs)
 
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  # LeViT
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+ LeViT-256 model pre-trained on ImageNet-1k at resolution 224x224. It was introduced in the paper [LeViT: a Vision Transformer in ConvNet's Clothing for Faster Inference
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  ](https://arxiv.org/abs/2104.01136) by Graham et al. and first released in [this repository](https://github.com/facebookresearch/LeViT).
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  Disclaimer: The team releasing LeViT did not write a model card for this model so this model card has been written by the Hugging Face team.
 
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  url = 'http://images.cocodataset.org/val2017/000000039769.jpg'
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  image = Image.open(requests.get(url, stream=True).raw)
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+ feature_extractor = LevitFeatureExtractor.from_pretrained('facebook/levit-256')
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+ model = LevitForImageClassificationWithTeacher.from_pretrained('facebook/levit-256')
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  inputs = feature_extractor(images=image, return_tensors="pt")
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  outputs = model(**inputs)