Add notebook.ipynb (powers HF Open-in-Colab button)

notebook.ipynb

@@ -0,0 +1,167 @@
+{
+ "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": "markdown",
+   "metadata": {},
+   "source": [
+    "# Rade-ASR-CTC-3B-fa — Persian Speech-to-Text\n",
+    "\n",
+    "Run Meta's **Omnilingual ASR CTC-3B**, fine-tuned on **Persian** by [Rade AI](https://huggingface.co/RadeAI).\n",
+    "\n",
+    "**Steps:** set a **GPU** runtime (`Runtime ▸ Change runtime type ▸ T4 GPU`), run **Cell 1**, then **`Runtime ▸ Restart session`**, then run the rest. Audio clips must be **< 40 s**.\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Cell 1 — install (then RESTART the session)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "metadata": {},
+   "execution_count": null,
+   "outputs": [],
+   "source": [
+    "!apt-get -qq install -y libsndfile1\n",
+    "!pip install -q omnilingual-asr huggingface_hub\n",
+    "# fairseq2 needs the CUDA 12.8 torch build; pin all three or you hit libcudart/torchvision errors\n",
+    "!pip install -q torch==2.8.0 torchaudio==2.8.0 torchvision==0.23.0 --index-url https://download.pytorch.org/whl/cu128\n",
+    "print('installed — now click Runtime ▸ Restart session, then run the cells below')\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## ⚠️ Now do `Runtime ▸ Restart session`, then continue ↓\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Cell 2 — check GPU\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "metadata": {},
+   "execution_count": null,
+   "outputs": [],
+   "source": [
+    "import torch\n",
+    "print('torch', torch.__version__, '| CUDA', torch.cuda.is_available(),\n",
+    "      torch.cuda.get_device_name(0) if torch.cuda.is_available() else 'NO GPU')\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Cell 3 — download the fine-tuned weights (single fp16 file, ~6.2 GB)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "metadata": {},
+   "execution_count": null,
+   "outputs": [],
+   "source": [
+    "from huggingface_hub import hf_hub_download\n",
+    "# single consolidated fp16 file — half the download of the fp32 shards, identical output\n",
+    "ckpt = hf_hub_download('RadeAI/Rade-ASR-CTC-3B-fa', 'model_fp16.pt')\n",
+    "print('weights at', ckpt)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Cell 4 — register the model with fairseq2\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "metadata": {},
+   "execution_count": null,
+   "outputs": [],
+   "source": [
+    "import pathlib\n",
+    "ad = pathlib.Path.home()/'.config/fairseq2/assets'; ad.mkdir(parents=True, exist_ok=True)\n",
+    "(ad/'rade.yaml').write_text(f'''name: rade_CTC_3B_fa\n",
+    "model_family: wav2vec2_asr\n",
+    "model_arch: 3b_v2\n",
+    "checkpoint: \"{ckpt}\"\n",
+    "tokenizer_ref: omniASR_tokenizer_written_v2\n",
+    "''')\n",
+    "print('asset card ready')\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Cell 5 — provide a Persian clip (< 40 s): upload a file\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "metadata": {},
+   "execution_count": null,
+   "outputs": [],
+   "source": [
+    "from google.colab import files\n",
+    "up = files.upload()\n",
+    "audio_path = list(up.keys())[0]\n",
+    "print('using', audio_path)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Cell 6 — transcribe 🎙️ → 📝\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "metadata": {},
+   "execution_count": null,
+   "outputs": [],
+   "source": [
+    "from omnilingual_asr.models.inference.pipeline import ASRInferencePipeline\n",
+    "pipe = ASRInferencePipeline(model_card='rade_CTC_3B_fa',\n",
+    "                            device='cuda' if torch.cuda.is_available() else 'cpu',\n",
+    "                            dtype=torch.float16)   # ~199x real time, 6.4 GB VRAM\n",
+    "text = pipe.transcribe([audio_path], lang=['pes_Arab'], batch_size=1)\n",
+    "print('📝', text[0])\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "---\n",
+    "Made by [Rade AI](https://huggingface.co/RadeAI) · base: [facebook/omniASR-CTC-3B](https://huggingface.co/facebook/omniASR-CTC-3B) · Apache-2.0\n"
+   ]
+  }
+ ]
+}