Update README.md
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@ -33,14 +33,17 @@ fine-tuned versions on a task that interests you.
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Here is how to use this model to classify an image of the COCO 2017 dataset into one of the 1,000 ImageNet classes:
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```python
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from transformers import BeitFeatureExtractor, BeitForImageClassification
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from transformers import BeitImageProcessor, BeitForImageClassification
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from PIL import Image
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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 = BeitFeatureExtractor.from_pretrained('microsoft/beit-base-patch16-224-pt22k-ft22k')
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processor = BeitImageProcessor.from_pretrained('microsoft/beit-base-patch16-224-pt22k-ft22k')
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model = BeitForImageClassification.from_pretrained('microsoft/beit-base-patch16-224-pt22k-ft22k')
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inputs = feature_extractor(images=image, return_tensors="pt")
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inputs = processor(images=image, return_tensors="pt")
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outputs = model(**inputs)
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logits = outputs.logits
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# model predicts one of the 21,841 ImageNet-22k classes
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