Fix typo

README.md

@@ -22,21 +22,20 @@ By pre-training the model, it learns an inner representation of images that can
 
 ## Intended uses & limitations
 
-You can use the raw model for image classification. See the [model hub](https://huggingface.co/models?search=google/vit) to look for
-fine-tuned versions on a task that interests you.
+You can use the raw model to embed images, but it's mostly intended to be fine-tuned on a downstream task.
 
 ### How to use
 
 Here is how to use this model:
 
 ```python
-from transformers import ViTFeatureExtractor, ViTForImageClassification
+from transformers import ViTFeatureExtractor, ViTModel
 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 = ViTFeatureExtractor.from_pretrained('google/vit-large-patch16-224-in21k')
-model = ViTForImageClassification.from_pretrained('google/vit-large-patch16-224-in21k')
+model = ViTModel.from_pretrained('google/vit-large-patch16-224-in21k')
 inputs = feature_extractor(images=image, return_tensors="pt")
 outputs = model(**inputs)
 last_hidden_state = outputs.last_hidden_state