Upload gradio_app.ipynb

gradio_app.ipynb

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+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "provenance": [],
+      "gpuType": "T4"
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    },
+    "language_info": {
+      "name": "python"
+    },
+    "accelerator": "GPU"
+  },
+  "cells": [
+    {
+      "cell_type": "code",
+      "execution_count": 4,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "KBOTNSWfwlMs",
+        "outputId": "0767243b-aaac-414b-bf15-5c37712777c8"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "/usr/local/lib/python3.11/dist-packages/huggingface_hub/utils/_auth.py:94: UserWarning: \n",
+            "The secret `HF_TOKEN` does not exist in your Colab secrets.\n",
+            "To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n",
+            "You will be able to reuse this secret in all of your notebooks.\n",
+            "Please note that authentication is recommended but still optional to access public models or datasets.\n",
+            "  warnings.warn(\n",
+            "Device set to use cuda:0\n"
+          ]
+        }
+      ],
+      "source": [
+        "from transformers import pipeline\n",
+        "\n",
+        "model_id = \"Gyaneshere/distilhubert-finetuned-gtzan\"\n",
+        "pipe = pipeline(\"audio-classification\", model=model_id)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "def classify_audio(filepath):\n",
+        "    preds = pipe(filepath)\n",
+        "    outputs = {}\n",
+        "    for p in preds:\n",
+        "        outputs[p[\"label\"]] = p[\"score\"]\n",
+        "    return outputs"
+      ],
+      "metadata": {
+        "id": "EDnsKBNTw21Y"
+      },
+      "execution_count": 5,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "import gradio as gr\n",
+        "\n",
+        "demo = gr.Interface(\n",
+        "    fn=classify_audio, inputs=gr.Audio(type=\"filepath\"), outputs=gr.Label()\n",
+        ")\n",
+        "demo.launch(debug=True)"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 648
+        },
+        "id": "bDO18TF_xAj0",
+        "outputId": "a2fd8a7b-d673-431c-a0ac-ed47813f3cf1"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Running Gradio in a Colab notebook requires sharing enabled. Automatically setting `share=True` (you can turn this off by setting `share=False` in `launch()` explicitly).\n",
+            "\n",
+            "Colab notebook detected. This cell will run indefinitely so that you can see errors and logs. To turn off, set debug=False in launch().\n",
+            "* Running on public URL: https://05087897ec4bd78398.gradio.live\n",
+            "\n",
+            "This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from the terminal in the working directory to deploy to Hugging Face Spaces (https://huggingface.co/spaces)\n"
+          ]
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<IPython.core.display.HTML object>"
+            ],
+            "text/html": [
+              "<div><iframe src=\"https://05087897ec4bd78398.gradio.live\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
+            ]
+          },
+          "metadata": {}
+        }
+      ]
+    }
+  ]
+}