initial commit

README.md

@@ -1,2 +1,7 @@
-# llava-on-sagemaker
-Deploy llava to sagemaker instantely
+# Llava On Sagemker
+
+Deploy llava to sagemaker instantely.
+
+Open the ./[llava.ipynb](llava.ipynb) notebook in Sagemaker Studio or in a Sagemaker Notebook and follow the instructions.
+
+![screenshot](screenshot.png)

llava.ipynb

@@ -0,0 +1,752 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Deploy LLaVA on Amazon Sagemaker"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[33mDEPRECATION: pyodbc 4.0.0-unsupported has a non-standard version number. pip 24.0 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of pyodbc or contact the author to suggest that they release a version with a conforming version number. Discussion can be found at https://github.com/pypa/pip/issues/12063\u001b[0m\u001b[33m\n",
+      "\u001b[0m\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n",
+      "\u001b[0m"
+     ]
+    }
+   ],
+   "source": [
+    "!pip install sagemaker --upgrade --quiet"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Deploy Llava"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "----------------!"
+     ]
+    }
+   ],
+   "source": [
+    "import sagemaker\n",
+    "from sagemaker.huggingface.model import HuggingFaceModel\n",
+    "\n",
+    "LLAVA_MODEL = \"s3://public-assets-vincent-claes/llava-v1.5-13b/model.tar.gz\"\n",
+    "\n",
+    "huggingface_model = HuggingFaceModel(\n",
+    "   model_data=LLAVA_MODEL,      # path to your model and script\n",
+    "   role=sagemaker.get_execution_role(), # iam role with permissions to create an Endpoint\n",
+    "   transformers_version=\"4.28.1\",  # transformers version used\n",
+    "   pytorch_version=\"2.0.0\",       # pytorch version used\n",
+    "   py_version='py310',            # python version used\n",
+    "   model_server_workers=1\n",
+    ")\n",
+    "\n",
+    "predictor = huggingface_model.deploy(\n",
+    "    initial_instance_count=1,\n",
+    "    instance_type=\"ml.g5.12xlarge\",\n",
+    "    container_startup_health_check_timeout=900, # increase timeout for large models\n",
+    "    model_data_download_timeout=900, # increase timeout for large models\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "### Call Llava"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The image features a small, red toy animal, possibly a stuffed animal or a figurine, with flames coming out of its back. The animal is wearing glasses, giving it a unique and eye-catching appearance. The flames are orange and yellow, adding a sense of warmth and energy to the scene. The overall color palette of the image is predominantly red, with the toy and the flames being the main sources of this color.\n"
+     ]
+    }
+   ],
+   "source": [
+    "import base64\n",
+    "import requests\n",
+    "\n",
+    "# URL of llava logo image\n",
+    "url = \"https://raw.githubusercontent.com/haotian-liu/LLaVA/main/images/llava_logo.png\"\n",
+    "\n",
+    "# Fetching the image from the URL\n",
+    "response = requests.get(url)\n",
+    "image_data = response.content\n",
+    "encoded_image = base64.b64encode(image_data).decode()\n",
+    "\n",
+    "# request\n",
+    "data = {\n",
+    "    \"image\" : encoded_image,\n",
+    "    \"question\" : \"Describe the image and color details.\",\n",
+    "}\n",
+    "output = predictor.predict(data)\n",
+    "print(output)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
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+  "availableInstances": [
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+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}