Update README.md

README.md

@@ -1,6 +1,5 @@
 ---
 license: apache-2.0
-tags:
 datasets:
 - imagenet
 ---
@@ -34,18 +33,18 @@ You can use the raw model for image classification. See the [model hub](https://
 Here is how to use this model in PyTorch:
 
 ```python
-from transformers import PerceiverFeatureExtractor, PerceiverForImageClassificationFourier
+from transformers import PerceiverImageProcessor, PerceiverForImageClassificationFourier
 import requests
 from PIL import Image
 
-feature_extractor = PerceiverFeatureExtractor.from_pretrained("deepmind/vision-perceiver-fourier")
+processor = PerceiverImageProcessor.from_pretrained("deepmind/vision-perceiver-fourier")
 model = PerceiverForImageClassificationFourier.from_pretrained("deepmind/vision-perceiver-fourier")
 
 url = "http://images.cocodataset.org/val2017/000000039769.jpg"
 image = Image.open(requests.get(url, stream=True).raw)
 
 # prepare input
-inputs = feature_extractor(image, return_tensors="pt").pixel_values
+inputs = processor(image, return_tensors="pt").pixel_values
 # forward pass
 outputs = model(inputs)
 logits = outputs.logits