app.py

import gradio as gr
from transformers import pipeline

pipe = pipeline("audio-classification", model="afern24/vit-beans-finetuned")

def classify_image(filepath):
    pred = pipe(filepath)
    outputs = {}
    for p in preds:
        outputs[p["label"]] = p["score"]
    return outputs

gr.Interface(fn=classify_image, input=gr.inputs.Image, outputs=gr.outputs.Label(num_top_classes=3), examples=[["leaf1.jpg"]]).load("models/afern24/vit-beans-finetuned").launch()