added title and description

app.py

@@ -128,9 +128,16 @@ def predict(img):
   results = {labels[label] : float(predictions[label]) for label in toplabels}
   return results
 
+description = """
+This is a space for Image Classfication using a Swin Transformer finetuned on the Food101 dataset with Timm and 🤗.
+You can find the model [here](https://huggingface.co/OmAlve/swin_s3_base_224-Foods-101)
+And the Notebook for finetuning [here](https://github.com/Om-Alve/Finetuning-CV-model/blob/main/Swin-Foods-101.ipynb)
+
+"""
 gr.Interface(fn=predict,
              inputs=gr.Image(type="pil"),
              outputs="label",
              examples=['./miso soup.jpg','./cupcake.jpg','./pasta.jpg'],
-             live=True).launch()
-
+             title="Food Classification with Swin Transformers",
+             description=description,
+             live=True).launch()