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import gradio as gr | |
from transformers import pipeline | |
# Load the pre-trained model | |
generator = pipeline("text-generation", model="EleutherAI/gpt-neo-2.7B") | |
# Define Gradio interface | |
def generate_response(prompt): | |
# Generate response based on the prompt | |
response = generator(prompt, max_length=50, do_sample=True, temperature=0.9) | |
return response[0]['generated_text'] | |
# Create Gradio interface | |
iface = gr.Interface( | |
fn=generate_response, | |
inputs="text", | |
outputs="text", | |
title="OpenAI Text Generation Model", | |
description="Enter a prompt and get a generated text response.", | |
) | |
# Deploy the Gradio interface | |
iface.launch(share=True) | |