app.py

import streamlit as st
from transformers import AutoTokenizer, AutoModelForSequenceClassification

# Load TinyBERT
model_name = "huawei-noah/TinyBERT_General_6L_768D"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSequenceClassification.from_pretrained(model_name)

# Streamlit App Title
st.title("TinyBERT Text Summarization")

# Input text box
input_text = st.text_area("Enter text for summarization:", height=200)

# Button to perform summarization
if st.button("Summarize"):
    if input_text:
        # Tokenize input text
        inputs = tokenizer(input_text, return_tensors="pt", truncation=True, padding=True)

        # Get model outputs
        outputs = model(**inputs)

        # Display output (this is placeholder logic, adjust to your specific task)
        st.write(f"Model output: {outputs}")
    else:
        st.warning("Please enter some text to summarize.")