app.py

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

id2label = {0: "Negative", 1: "Positive"}
label2id = {"Negative":0, "Positive":1}

# Load the tokenizer and model
tokenizer = AutoTokenizer.from_pretrained('distilbert/distilbert-base-uncased', add_prefix_space=True)
model = AutoModelForSequenceClassification.from_pretrained('AmirRghp/distilbert-base-uncasedimdb-text-classification')

# Create the pipeline
classifier = pipeline('text-classification', model=model, tokenizer=tokenizer)


def classify_text(text):
    result = classifier(text)
    return result

gr.Interface(fn=classify_text, inputs="text", outputs="json").launch()