app.py

import gradio as gr
import torch
from transformers import AutoModelForSequenceClassification,AutoTokenizer,pipeline

model = AutoModelForSequenceClassification.from_pretrained('SeyedAli/Persian-Text-Sentiment-Bert-V1')
tokenizer = AutoTokenizer.from_pretrained('SeyedAli/Persian-Text-Sentiment-Bert-V1')

def Sentiment(text):
    pipline = pipeline(task="text-classification", model=model, tokenizer=tokenizer)
    preds=pipline(text)
    # return output
    outputs = {}
    for p in preds:
        outputs[p["label"]] = p["score"]
    return outputs

iface = gr.Interface(fn=Sentiment, inputs="text", outputs=gr.outputs.Label())
iface.launch(share=False)