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import streamlit as st
from transformers import pipeline
# Initialize the text generation pipeline with optimizations
pipe = pipeline(
"text-generation",
model="Qwen/Qwen2.5-0.5B-Instruct",
device=-1, # Ensure it runs on CPU
use_fast=True, # Use fast tokenizer
)
# Streamlit app
st.title("Qwen Model Chat")
# Text input from the user
user_input = st.text_input("Enter your message:", "Delete this and write your query?")
# Generate text when the button is clicked
if st.button("Generate"):
messages = [{"role": "user", "content": user_input}]
# Reduce max_new_tokens for faster generation
output = pipe(messages, max_new_tokens=150) # Adjust as needed for speed
generated_text = output[0]['generated_text']
# Display the generated text
st.write("Generated Response:")
st.write(generated_text)