revert: restore train_origami.ipynb to Prasanna's exact version

training/train_origami.ipynb

@@ -334,20 +334,6 @@
     "print(f\"shape_match — bad: {shape_match(test_bad)}\")"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "id": "nr66p2kwvys",
-   "source": "## 8. Train on Modal (recommended)\n\nRun training on Modal instead of this Colab runtime — B200 GPU, Qwen3-32B BF16, no quantization needed.\n\nThe env server is already running on Railway so Modal just needs the URL.",
-   "metadata": {}
-  },
-  {
-   "cell_type": "code",
-   "id": "zzuilajxe08",
-   "source": "import subprocess, sys, os\n\n# Install Modal if needed\nsubprocess.run([sys.executable, \"-m\", \"pip\", \"install\", \"-q\", \"modal\"], check=True)\n\n# Authenticate (opens browser on first run — skip if already authed)\n# subprocess.run([\"modal\", \"setup\"], check=True)\n\n# Point Modal at the already-running Railway env server\nRAILWAY_URL = \"https://origami-env-production.up.railway.app\"\n\nresult = subprocess.run(\n    [\n        \"modal\", \"run\", \"modal_train.py\",\n        \"--task\", \"all\",\n        \"--max-steps\", \"600\",\n        \"--server-url\", RAILWAY_URL,\n    ],\n    cwd=os.path.dirname(os.path.abspath(\"modal_train.py\")),  # repo root\n)\nprint(\"Exit code:\", result.returncode)",
-   "metadata": {},
-   "execution_count": null,
-   "outputs": []
-  },
   {
    "cell_type": "markdown",
    "id": "trainer_header",