Update README.md

README.md

@@ -37,17 +37,17 @@ 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 ConvNextFeatureExtractor, ConvNextForImageClassification
+from transformers import ConvNextImageProcessor, ConvNextForImageClassification
 import torch
 from datasets import load_dataset
 
 dataset = load_dataset("huggingface/cats-image")
 image = dataset["test"]["image"][0]
 
-feature_extractor = ConvNextFeatureExtractor.from_pretrained("facebook/convnext-xlarge-384-22k-1k")
+processor = ConvNextImageProcessor.from_pretrained("facebook/convnext-xlarge-384-22k-1k")
 model = ConvNextForImageClassification.from_pretrained("facebook/convnext-xlarge-384-22k-1k")
 
-inputs = feature_extractor(image, return_tensors="pt")
+inputs = processor(image, return_tensors="pt")
 
 with torch.no_grad():
     logits = model(**inputs).logits