Update README.md

README.md

@@ -35,16 +35,16 @@ You can use the raw model for encoding document images into a vector space, but
 Here is how to use this model in PyTorch:
 
 ```python
-from transformers import AutoFeatureExtractor, AutoModelForImageClassification
+from transformers import AutoImageProcessor, AutoModelForImageClassification
 import torch
 from PIL import Image
 
 image = Image.open('path_to_your_document_image').convert('RGB')
 
-feature_extractor = AutoFeatureExtractor.from_pretrained("microsoft/dit-base-finetuned-rvlcdip")
+processor = AutoImageProcessor.from_pretrained("microsoft/dit-base-finetuned-rvlcdip")
 model = AutoModelForImageClassification.from_pretrained("microsoft/dit-base-finetuned-rvlcdip")
 
-inputs = feature_extractor(images=image, return_tensors="pt")
+inputs = processor(images=image, return_tensors="pt")
 outputs = model(**inputs)
 logits = outputs.logits