demos/interface_series_load/run.ipynb

{"cells": [{"cell_type": "markdown", "id": 302934307671667531413257853548643485645, "metadata": {}, "source": ["# Gradio Demo: interface_series_load"]}, {"cell_type": "code", "execution_count": null, "id": 272996653310673477252411125948039410165, "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": 288918539441861185822528903084949547379, "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "import numpy as np\n", "\n", "generator = gr.load(\"huggingface/gpt2\")\n", "\n", "\n", "translator = gr.Interface(lambda s: \"https://gradio-builds.s3.amazonaws.com/diffusion_image/cute_dog.jpg\", gr.Textbox(), gr.Image())\n", "\n", "demo = gr.Series(generator, translator, description=\"This demo combines two Spaces: a text generator (`huggingface/gpt2`) and a text translator (`huggingface/t5-small`). The first Space takes a prompt as input and generates a text. The second Space takes the generated text as input and translates it into another language.\")\n", "\n", "if __name__ == \"__main__\":\n", "    demo.launch()"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}