Fix typo

README.md

@@ -26,18 +26,18 @@ fine-tuned versions on a task that interests you.
 
 ### How to use
 
-Since this model is a distilled ViT model, you can plug it into DeiTModel or DeiTForImageClassification. Note that the model expects the data to be prepared using DeiTFeatureExtractor. Here we use AutoFeatureExtractor, which will automatically use the appropriate feature extractor given the model name. 
+Since this model is a distilled ViT model, you can plug it into DeiTModel, DeiTForImageClassification or DeiTForImageClassificationWithTeacher. Note that the model expects the data to be prepared using DeiTFeatureExtractor. Here we use AutoFeatureExtractor, which will automatically use the appropriate feature extractor given the model name. 
 
 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 AutoFeatureExtractor, DeiTForImageClassification
+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 = DeiTForImageClassification.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")
 outputs = model(**inputs)
 logits = outputs.logits