app.py

import gradio as gr
from transformers import pipeline

#pipeline = pipeline(task="image-classification", model="julien-c/hotdog-not-hotdog")
#pipeline = pipeline(task="image-classification", model="C:\hotdog-not-hotdog")
pipeline = pipeline(task="image-classification", model="chennaiai/my-hotdog-not-hotdog")

print("<<<<<< App is running >>>>>>")

def predict(image):
    predictions = pipeline(image)
    return {p["label"]:p["score"] for p in predictions}

gr.Interface(predict,
      inputs=gr.inputs.Image(label="Upload hot dog candidate", type="filepath"),
      outputs=gr.outputs.Label(num_top_classes=2),
      title="Hot Dog? Or Not?",
      allow_flagging="manual"
      ).launch()