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import gradio as gr | |
from transformers import pipeline | |
# Load the GPT-2 model from Hugging Face using the pipeline | |
generator = pipeline('text-generation', model='gpt2-medium') | |
def generate_text(prompt, max_length=50): | |
# Generate text using the GPT-2 model | |
generated_text = generator(prompt, max_length=max_length, num_return_sequences=1)[0]['generated_text'] | |
return generated_text | |
# Create a Gradio interface | |
iface = gr.Interface( | |
fn=generate_text, | |
inputs=[ | |
gr.Textbox(lines=3, placeholder="Enter your prompt here...", label="Prompt"), | |
gr.Slider(minimum=10, maximum=250, value=100, label="Max Length"), | |
], | |
outputs=gr.Textbox(label="Generated Text"), | |
title="GPT-2 Text Generator (OUTDATED)", | |
description="Enter a prompt and generate text using GPT-2 on Hugging Face. Try out other models [here](https://huggingface.co/tchans123)." | |
) | |
# Launch the Gradio interface | |
iface.launch(share=True) | |