Make code example more clear

README.md

@@ -33,13 +33,19 @@ Here is how to use this model to classify an image of the COCO 2017 dataset into
 from transformers import AutoFeatureExtractor, DeiTForImageClassificationWithTeacher
 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('facebook/deit-base-distilled-patch16-224')
 model = DeiTForImageClassificationWithTeacher.from_pretrained('facebook/deit-base-distilled-patch16-224')
+
 inputs = feature_extractor(images=image, return_tensors="pt")
+
+# forward pass
 outputs = model(**inputs)
 logits = outputs.logits
+
 # model predicts one of the 1000 ImageNet classes
 predicted_class_idx = logits.argmax(-1).item()
 print("Predicted class:", model.config.id2label[predicted_class_idx])