run.ipynb

{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: text_generation\n", "### This text generation demo takes in input text and returns generated text. It uses the Transformers library to set up the model and has two examples.\n", "        "]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio git+https://github.com/huggingface/transformers gradio torch"]}, {"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):\n", "    result = generator(text, max_length=30, num_return_sequences=1)\n", "    return result[0][\"generated_text\"]  # type: ignore\n", "\n", "examples = [\n", "    [\"The Moon's orbit around Earth has\"],\n", "    [\"The smooth Borealis basin in the Northern Hemisphere covers 40%\"],\n", "]\n", "\n", "demo = gr.Interface(\n", "    fn=generate,\n", "    inputs=gr.Textbox(lines=5, label=\"Input Text\"),\n", "    outputs=gr.Textbox(label=\"Generated Text\"),\n", "    examples=examples\n", ")\n", "\n", "demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}