app.py

import gradio as gr
from transformers import AutoTokenizer, AutoModelForSequenceClassification

# Load pre-trained model and tokenizer
model_name = "nlptown/bert-base-multilingual-uncased-sentiment"
model = AutoModelForSequenceClassification.from_pretrained(model_name)
tokenizer = AutoTokenizer.from_pretrained(model_name)

def predict(text):
    # Tokenize input text
    inputs = tokenizer(text, return_tensors="pt")

    # Get model's prediction
    outputs = model(**inputs)

    # Get predicted class index
    predicted_class_idx = outputs.logits.argmax(-1).item()

    # Return predicted class
    return model.config.id2label[predicted_class_idx]

iface = gr.Interface(fn=predict, inputs="text", outputs="text")
iface.launch(share=True)