app.py

import streamlit as st
from transformers import DistilBertTokenizer, DistilBertForSequenceClassification
import torch

st.title("Multi classification Fine tunning model")

# Load model and tokenizer
model_dir = "distilbert_fine_tuned_model"
tokenizer = DistilBertTokenizer.from_pretrained(model_dir)
model = DistilBertForSequenceClassification.from_pretrained(model_dir)

def predict_class(text):
    inputs = tokenizer(text, return_tensors="pt", truncation=True, padding=True, max_length=512)

    outputs = model(**inputs)
    
    prediction_value = torch.argmax(outputs.logits, dim=1).item()

    stars=[" 1 stars"," 2 stars"," 3 stars"," 4 stars"," 5 stars"]
    st.write(stars[prediction_value])

inputs_text=st.text_input("Please enter the text",value="I think I really like this place. Ayesha and I had a chance to visit  Cheuvront on a Monday night. It wasn\'t terribly busy when we arrived and we were warmly greeted. Unfortunately we were seated next to a loud group of young children that thought they knew something of the world ")

if st.button("submit"):
    predict_class(inputs_text)