{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: unified_demo_text_generation"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio torch transformers"]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "from transformers import pipeline\n", "\n", "generator = pipeline('text-generation', model = 'gpt2')\n", "\n", "def generate_text(text_prompt):\n", "  response = generator(text_prompt, max_length = 30, num_return_sequences=5)\n", "  return response[0]['generated_text']\n", "\n", "textbox = gr.Textbox()\n", "\n", "demo = gr.Interface(generate_text, textbox, textbox)\n", "\n", "if __name__ == \"__main__\":\n", "    demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}