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Update README.md

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Niels Rogge 2023-02-27 15:08:16 +00:00 committed by huggingface-web
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@ -33,14 +33,17 @@ fine-tuned versions on a task that interests you.
Here is how to use this model to classify an image of the COCO 2017 dataset into one of the 1,000 ImageNet classes: Here is how to use this model to classify an image of the COCO 2017 dataset into one of the 1,000 ImageNet classes:
```python ```python
from transformers import BeitFeatureExtractor, BeitForImageClassification from transformers import BeitImageProcessor, BeitForImageClassification
from PIL import Image from PIL import Image
import requests import requests
url = 'http://images.cocodataset.org/val2017/000000039769.jpg' url = 'http://images.cocodataset.org/val2017/000000039769.jpg'
image = Image.open(requests.get(url, stream=True).raw) image = Image.open(requests.get(url, stream=True).raw)
feature_extractor = BeitFeatureExtractor.from_pretrained('microsoft/beit-base-patch16-224-pt22k-ft22k')
processor = BeitImageProcessor.from_pretrained('microsoft/beit-base-patch16-224-pt22k-ft22k')
model = BeitForImageClassification.from_pretrained('microsoft/beit-base-patch16-224-pt22k-ft22k') model = BeitForImageClassification.from_pretrained('microsoft/beit-base-patch16-224-pt22k-ft22k')
inputs = feature_extractor(images=image, return_tensors="pt")
inputs = processor(images=image, return_tensors="pt")
outputs = model(**inputs) outputs = model(**inputs)
logits = outputs.logits logits = outputs.logits
# model predicts one of the 21,841 ImageNet-22k classes # model predicts one of the 21,841 ImageNet-22k classes