tasks/generative-ai/text-to-text/fine-tuning/instruction-tuning/Transformers/Rinna_Neox_Inference_ja.ipynb

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 "cells": [
  {
   "cell_type": "markdown",
   "id": "f24a09e9-262f-4943-84a2-b60b6c24c389",
   "metadata": {},
   "source": [
    "# Rinna NeoX SageMaker Inference\n",
    "\n",
    "This is a sample code to deploy [Rinna NeoX](https://huggingface.co/rinna/japanese-gpt-neox-3.6b-instruction-sft) on SageMaker."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0428530b-8f42-4ab7-83ce-c3bdfa96a51b",
   "metadata": {},
   "outputs": [],
   "source": [
    "!pip install \"sagemaker>=2.143.0\" -U"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3f94c4e8-de95-4657-97e0-dc213415bee5",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import sagemaker, boto3, json\n",
    "from sagemaker import get_execution_role\n",
    "from sagemaker.pytorch.model import PyTorchModel\n",
    "from sagemaker.huggingface import HuggingFace\n",
    "\n",
    "role = get_execution_role()\n",
    "region = boto3.Session().region_name\n",
    "sess = sagemaker.Session()\n",
    "bucket = sess.default_bucket()\n",
    "\n",
    "sagemaker.__version__"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9882e8b3-4b8a-4700-8233-8f7e504c6b8d",
   "metadata": {},
   "source": [
    "## Package and Upload Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a08d3c5f-2537-433b-a7c9-e2da3480a5f4",
   "metadata": {
    "scrolled": true,
    "tags": []
   },
   "outputs": [],
   "source": [
    "!rm -rf scripts/model\n",
    "%cd scripts\n",
    "!tar -czvf ../package.tar.gz *\n",
    "%cd -"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "11d0ae99-8cfe-43f5-8677-863e91bce7a0",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "model_path = sess.upload_data('package.tar.gz', bucket=bucket, key_prefix=f\"Rinna-Inference\")\n",
    "model_path"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6432b637-a883-4d94-ba28-54fc1be73408",
   "metadata": {},
   "source": [
    "## Deploy Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a20f1592-7ff0-45a2-bbb7-3f9528a11a98",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "from sagemaker.async_inference import AsyncInferenceConfig\n",
    "from sagemaker.serializers import JSONSerializer\n",
    "\n",
    "endpoint_name = \"Rinna-Inference\"\n",
    "\n",
    "huggingface_model = PyTorchModel(\n",
    "    model_data=model_path,\n",
    "    framework_version=\"2.0\",\n",
    "    py_version='py310',\n",
    "    role=role,\n",
    "    name=endpoint_name,\n",
    "    env={\n",
    "        \"model_params\": json.dumps({\n",
    "            \"base_model\": \"rinna/japanese-gpt-neox-3.6b-instruction-ppo\",\n",
    "            \"peft\": False,\n",
    "            \"load_4bit\": False,\n",
    "            \"use_deepspeed\": True,\n",
    "            \"use_optimum\": True,\n",
    "            \"prompt_template\": \"rinna\",\n",
    "        }),\n",
    "        \"SAGEMAKER_MODEL_SERVER_TIMEOUT\": \"3600\"\n",
    "    }\n",
    ")\n",
    "\n",
    "# deploy model to SageMaker Inference\n",
    "predictor = huggingface_model.deploy(\n",
    "    initial_instance_count=1,\n",
    "    instance_type='ml.g4dn.xlarge',\n",
    "    endpoint_name=endpoint_name,\n",
    "    serializer=JSONSerializer(),\n",
    "    # async_inference_config=AsyncInferenceConfig()\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d07b0901-2675-49e5-8ccd-968f3ca2820e",
   "metadata": {},
   "source": [
    "## Run Inference"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b6eb4904-4b77-4cd0-bbe9-4d4685bc018e",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "from sagemaker.predictor import Predictor\n",
    "from sagemaker.predictor_async import AsyncPredictor\n",
    "from sagemaker.serializers import JSONSerializer\n",
    "from sagemaker.deserializers import NumpyDeserializer, JSONDeserializer\n",
    "\n",
    "predictor_client=Predictor(\n",
    "    endpoint_name=endpoint_name,\n",
    "    sagemaker_session=sess,\n",
    "    serializer=JSONSerializer(),\n",
    "    deserializer=JSONDeserializer()\n",
    ")\n",
    "# predictor_client = AsyncPredictor(\n",
    "#     predictor=predictor_client,\n",
    "#     name=endpoint_name\n",
    "# )\n",
    "data = {\n",
    "    \"instruction\": \"\"\"ヴァージン・オーストラリアはいつから運航を開始したのですか？\"\"\".replace(\"\\n\", \"<NL>\"),  # システム\n",
    "    \"input\": \"\"\"ヴァージン・オーストラリア航空（Virgin Australia Airlines Pty Ltd）の商号で、オーストラリアを拠点とする航空会社です。ヴァージン・ブランドを使用する航空会社の中で、保有機材数では最大の航空会社である。2000年8月31日にヴァージン・ブルーとして、2機の航空機で単一路線で運航を開始した[3]。2001年9月のアンセット・オーストラリアの破綻後、突然オーストラリア国内市場の大手航空会社としての地位を確立した。その後、ブリスベン、メルボルン、シドニーをハブとして、オーストラリア国内の32都市に直接乗り入れるまでに成長した[4]。\"\"\".replace(\"\\n\", \"<NL>\"),  # ユーザー\n",
    "    \"max_new_tokens\": 128,\n",
    "    \"temperature\": 0.7,\n",
    "    \"do_sample\": True,\n",
    "    \"pad_token_id\": 0,\n",
    "    \"bos_token_id\": 2,\n",
    "    \"eos_token_id\": 3,\n",
    "    # \"stop_ids\": [50278, 50279, 50277, 1, 0],\n",
    "}\n",
    "response = predictor_client.predict(\n",
    "    data=data\n",
    ")\n",
    "print(response.replace(\"<NL>\", \"\\n\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "219ebbfd-3b41-4305-95af-8d35c013969b",
   "metadata": {},
   "source": [
    "## Delete Endpoint"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1cd9be37-f988-4394-b920-61d1cfeaf066",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "predictor.delete_model()\n",
    "predictor.delete_endpoint()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b34d15bf-6c19-4446-8108-f07c9b365f19",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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