Add app

app.py

@@ -0,0 +1,18 @@
+from transformers import pipeline
+import gradio as gr
+
+pipe = pipeline(
+    "audio-classification", model="Davidmide02/distilhubert-finetuned-gtzan"
+)
+
+def classify_audio(filepath):
+    preds = pipe(filepath)
+    outputs = {}
+    for p in preds:
+        outputs[p["label"]] = p["score"]
+    return outputs
+
+demo = gr.Interface(
+    fn=classify_audio, inputs=gr.Audio(type="filepath"), outputs=gr.Label()
+)
+demo.launch(debug=True)

note.ipynb

@@ -0,0 +1,103 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from transformers import pipeline\n",
+    "\n",
+    "pipe = pipeline(\n",
+    "    \"audio-classification\", model=\"Davidmide02/distilhubert-finetuned-gtzan\"\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "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"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Running on local URL:  http://127.0.0.1:7860\n",
+      "\n",
+      "To create a public link, set `share=True` in `launch()`.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div><iframe src=\"http://127.0.0.1:7860/\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Keyboard interruption in main thread... closing server.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": []
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "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": {
+  "kernelspec": {
+   "display_name": ".venv",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}