gradio/demo/ner_pipeline/run.ipynb

{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: ner_pipeline"]}, {"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": ["from transformers import pipeline\n", "\n", "import gradio as gr\n", "\n", "ner_pipeline = pipeline(\"ner\")\n", "\n", "examples = [\n", "    \"Does Chicago have any stores and does Joe live here?\",\n", "]\n", "\n", "def ner(text):\n", "    output = ner_pipeline(text)\n", "    return {\"text\": text, \"entities\": output}\n", "\n", "demo = gr.Interface(ner,\n", "             gr.Textbox(placeholder=\"Enter sentence here...\"),\n", "             gr.HighlightedText(),\n", "             examples=examples)\n", "\n", "if __name__ == \"__main__\":\n", "    demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}