Update README.md

README.md

@@ -40,17 +40,17 @@ 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:
 
 ```python
-from transformers import AutoFeatureExtractor, SwinForImageClassification
+from transformers import AutoImageProcessor, AutoModelForImageClassification
 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("microsoft/swinv2-tiny-patch4-window8-256")
-model = SwinForImageClassification.from_pretrained("microsoft/swinv2-tiny-patch4-window8-256")
+processor = AutoImageProcessor.from_pretrained("microsoft/swinv2-tiny-patch4-window8-256")
+model = AutoModelForImageClassification.from_pretrained("microsoft/swinv2-tiny-patch4-window8-256")
 
-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