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import streamlit as st
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
# Load the tokenizer and model (change 'model_name' to your specific model)
model_name = "gpt2" # Replace with your model
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)
# Function to generate a response
def generate_response(prompt):
if not prompt:
return "Please enter a prompt."
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
output = model.generate(**inputs, max_new_tokens=512)
response = tokenizer.decode(output[0], skip_special_tokens=True)
return response
# Streamlit UI
st.title("AI Text Generator")
prompt = st.text_area("Enter your prompt:", placeholder="Type your question or prompt here...")
if st.button("Generate Response"):
with st.spinner("Generating response..."):
response = generate_response(prompt)
st.text_area("Model Response:", value=response, height=200, disabled=True)
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