Update README.md

README.md

@@ -39,14 +39,14 @@ It achieves the following results on the evaluation set:
 
 ## Model description
 
-This model is a fine-tuned version of , which is a Vision Transformer (ViT)
+This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224), which is a Vision Transformer (ViT)
 ViT model is originaly a transformer encoder model pre-trained and fine-tuned on ImageNet 2012. 
 It was introduced in the paper "An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale" by Dosovitskiy et al. 
 The model processes images as sequences of 16x16 patches, adding a [CLS] token for classification tasks, and uses absolute position embeddings. Pre-training enables the model to learn rich image representations, which can be leveraged for downstream tasks by adding a linear classifier on top of the [CLS] token. The weights were converted from the timm repository by Ross Wightman.
 
 ## Intended uses & limitations
 
-More information needed
+This must be used for classification of x-ray images of the brain to diagnose of brain tumor.
 
 ## Training and evaluation data