Add notebook

notebook.ipynb

@@ -0,0 +1,67 @@
+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "machine_shape": "hm",
+      "gpuType": "T4",
+      "provenance": []
+    },
+    "accelerator": "GPU",
+    "kaggle": {
+      "accelerator": "gpu"
+    },
+    "language_info": {
+      "name": "python"
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    }
+  },
+  "cells": [
+    {
+      "cell_type": "code",
+      "source": [
+        "!pip install -U transformers"
+      ],
+      "metadata": {
+        "id": "4LXugJ1wUN5o"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "## Local Inference on GPU\n",
+        "Model page: https://huggingface.co/vikhyatk/moondream2\n",
+        "\n",
+        "⚠️ If the generated code snippets do not work, please open an issue on either the [model repo](https://huggingface.co/vikhyatk/moondream2)\n",
+        "\t\t\tand/or on [huggingface.js](https://github.com/huggingface/huggingface.js/blob/main/packages/tasks/src/model-libraries-snippets.ts) 🙏"
+      ],
+      "metadata": {
+        "id": "t490XrsVUN5q"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "from transformers import AutoModelForCausalLM, AutoTokenizer\n",
+        "\n",
+        "tokenizer = AutoTokenizer.from_pretrained(\"vikhyatk/moondream2\")\n",
+        "model = AutoModelForCausalLM.from_pretrained(\n",
+        "    \"vikhyatk/moondream2\",\n",
+        "    revision=\"2025-06-21\",\n",
+        "    trust_remote_code=True,\n",
+        "    device_map={\"\": \"cuda\"}\n",
+        ")"
+      ],
+      "metadata": {
+        "id": "6aWNuxB8UN5s"
+      },
+      "execution_count": null,
+      "outputs": []
+    }
+  ]
+}