diff --git a/notebooks/kernel-metadata.json b/notebooks/kernel-metadata.json
new file mode 100644
index 0000000..3f07f9c
--- /dev/null
+++ b/notebooks/kernel-metadata.json
@@ -0,0 +1,13 @@
+{
+  "id": "nvandessel/hippofloop",
+  "title": "hippofloop",
+  "code_file": "train-hippofloop.ipynb",
+  "language": "python",
+  "kernel_type": "notebook",
+  "is_private": true,
+  "enable_gpu": true,
+  "enable_internet": true,
+  "dataset_sources": ["nvandessel/floop-decisions"],
+  "competition_sources": [],
+  "kernel_sources": []
+}
diff --git a/notebooks/train-hippofloop.ipynb b/notebooks/train-hippofloop.ipynb
index d7f70fc..0c56293 100644
--- a/notebooks/train-hippofloop.ipynb
+++ b/notebooks/train-hippofloop.ipynb
@@ -51,28 +51,14 @@
   {
    "cell_type": "markdown",
    "metadata": {},
-   "source": [
-    "## 2. Load and explore data\n",
-    "\n",
-    "Data is expected as a Kaggle Dataset mounted at `/kaggle/input/floop-decisions/`.\n",
-    "Upload your `decisions.jsonl` files there."
-   ]
+   "source": "## 2. Load and explore data\n\nData is expected as a Kaggle Dataset. The path is auto-detected."
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
-   "source": [
-    "DATA_DIR = Path(\"/kaggle/input/floop-decisions\")\n",
-    "\n",
-    "# Find all JSONL files in the dataset\n",
-    "jsonl_files = sorted(DATA_DIR.glob(\"*.jsonl\"))\n",
-    "print(f\"Found {len(jsonl_files)} JSONL files:\")\n",
-    "for f in jsonl_files:\n",
-    "    size_mb = f.stat().st_size / (1024 * 1024)\n",
-    "    print(f\"  {f.name} ({size_mb:.1f} MB)\")"
-   ]
+   "source": "# Auto-detect Kaggle dataset path\n_candidates = [\n    Path(\"/kaggle/input/datasets/nvandessel/floop-decisions\"),\n    Path(\"/kaggle/input/floop-decisions\"),\n]\nDATA_DIR = next((p for p in _candidates if p.exists()), None)\nif DATA_DIR is None:\n    raise FileNotFoundError(\n        f\"Kaggle dataset not found. Checked: {[str(p) for p in _candidates]}. \"\n        \"Add the 'floop-decisions' dataset in the notebook sidebar.\"\n    )\nprint(f\"Data dir: {DATA_DIR}\")\n\n# Find all JSONL files in the dataset\njsonl_files = sorted(DATA_DIR.glob(\"*.jsonl\"))\nif not jsonl_files:\n    raise FileNotFoundError(f\"No .jsonl files found in {DATA_DIR}\")\nprint(f\"Found {len(jsonl_files)} JSONL files:\")\nfor f in jsonl_files:\n    size_mb = f.stat().st_size / (1024 * 1024)\n    print(f\"  {f.name} ({size_mb:.1f} MB)\")"
   },
   {
    "cell_type": "code",