Update README.md

README.md

@@ -7,18 +7,18 @@ A fine-tuned version of ViT-base on a collected set of Pokémon images. You can
 # Using the model
 
 ```python
-from transformers import ViTForImageClassification, ViTFeatureExtractor
+from transformers import ViTForImageClassification, ViTImageProcessor
 from PIL import Image
 import torch
 
 # Loading in Model
 device = "cuda" if torch.cuda.is_available() else "cpu"
 model = ViTForImageClassification.from_pretrained( "imjeffhi/pokemon_classifier").to(device)
-feature_extractor = ViTFeatureExtractor.from_pretrained('imjeffhi/pokemon_classifier')
+image_processor = ViTImageProcessor.from_pretrained('imjeffhi/pokemon_classifier')
 
 # Caling the model on a test image
 img = Image.open('test.jpg')
-extracted = feature_extractor(images=img, return_tensors='pt').to(device)
+extracted = image_processor(images=img, return_tensors='pt').to(device)
 predicted_id = model(**extracted).logits.argmax(-1).item()
 predicted_pokemon = model.config.id2label[predicted_id]
 ```