Update README.md

README.md

@@ -31,15 +31,15 @@ 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:
 
 ```python
-from transformers import ViTHybridFeatureExtractor, ViTHybridForImageClassification
+from transformers import ViTHybridImageProcessor, ViTHybridForImageClassification
 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 = ViTHybridFeatureExtractor.from_pretrained('google/vit-base-patch16-224')
-model = ViTHybridForImageClassification.from_pretrained('google/vit-base-patch16-224')
+feature_extractor = ViTHybridImageProcessor.from_pretrained('google/vit-hybrid-base-bit-384')
+model = ViTHybridForImageClassification.from_pretrained('google/vit-hybrid-base-bit-384')
 
 inputs = feature_extractor(images=image, return_tensors="pt")
 outputs = model(**inputs)