Create app.py

app.py

@@ -0,0 +1,27 @@
+import gradio as gr
+
+from huggingface_hub import HfApi, hf_hub_download
+from transformers import model
+
+def get_model_ids():
+    api = HfApi()
+    models = api.list_models(filter="llama-leaderboard")
+    model_ids = [x.modelId for x in models]
+    return model_ids
+    
+models = {}
+for model_id in get_model_ids():
+  models[model_id] = pipeline("image-classification", model=model_id)
+    
+def predict(img, model_id):
+  return models[model_id](img)
+  
+gr.Interface(
+  fn=predict, 
+   inputs=[
+     gr.inputs.Image(type="pil"),
+     gradio.inputs.Dropdown(get_model_ids())
+   ]
+   outputs=gr.outputs.Label(num_top_classes=3),
+   examples=["llama.jpg", "potato.jpg"]
+).launch()