Update README.md

README.md

@@ -34,14 +34,14 @@ Since this model is a more efficiently trained ViT model, you can plug it into V
 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
-from transformers import AutoFeatureExtractor, ViTForImageClassification
+from transformers import AutoImageProcessor, ViTForImageClassification
 from PIL import Image
 import requests
 url = 'http://images.cocodataset.org/val2017/000000039769.jpg'
 image = Image.open(requests.get(url, stream=True).raw)
-feature_extractor = AutoFeatureExtractor.from_pretrained('facebook/deit-tiny-patch16-224')
+processor = AutoImageProcessor.from_pretrained("facebook/deit-tiny-patch16-224")
 model = ViTForImageClassification.from_pretrained('facebook/deit-tiny-patch16-224')
-inputs = feature_extractor(images=image, return_tensors="pt")
+inputs = processor(images=image, return_tensors="pt")
 outputs = model(**inputs)
 logits = outputs.logits
 # model predicts one of the 1000 ImageNet classes