Updated fine-tuning workshop

workshops/fine-tuning-with-sagemakerai-and-bedrock/task_01_foundation_model_playground/01.01_search_and_deploy_huggingface_llm.ipynb

@@ -15,14 +15,16 @@
    "id": "fcbb5d61-8a0b-47d9-a7c5-0c041c82b8bf",
    "metadata": {},
    "source": [
-    "# 🚀 Deploy `deepseek-ai/DeepSeek-R1-Distill-Llama-8B` on Amazon SageMaker"
+    "# 🚀 Deploy `Qwen/Qwen3-4B-Instruct-2507` on Amazon SageMaker"
    ]
   },
   {
    "cell_type": "markdown",
    "id": "dd210e90-21e1-4f03-a08e-c3fba9aa6979",
    "metadata": {},
    "source": [
+    "## Prerequisites\n",
+    "\n",
     "To start off, let's install some packages to help us through the notebooks. **Restart the kernel after packages have been installed.**"
    ]
   },
@@ -57,6 +59,14 @@
     "get_ipython().kernel.do_shutdown(True)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "a947367a-bea3-498a-9548-d6e6e08f0d10",
+   "metadata": {},
+   "source": [
+    "***"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -66,9 +76,9 @@
    "source": [
     "import os\n",
     "import sagemaker\n",
-    "from sagemaker.djl_inference import DJLModel\n",
-    "from ipywidgets import Dropdown\n",
-    "\n",
+    "import boto3\n",
+    "import shutil\n",
+    "from sagemaker.config import load_sagemaker_config\n",
     "import sys\n",
     "sys.path.append(os.path.dirname(os.getcwd()))\n",
     "\n",
@@ -78,31 +88,20 @@
     "    print_dialog,\n",
     "    format_messages,\n",
     "    write_eula\n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "8b53f21c-3a65-44fc-b547-712d971cd652",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import boto3\n",
-    "import shutil\n",
-    "import sagemaker\n",
-    "from sagemaker.config import load_sagemaker_config\n",
+    ")\n",
     "\n",
     "sagemaker_session = sagemaker.Session()\n",
     "s3_client = boto3.client('s3')\n",
     "\n",
+    "region = sagemaker_session.boto_session.region_name\n",
     "bucket_name = sagemaker_session.default_bucket()\n",
     "default_prefix = sagemaker_session.default_bucket_prefix\n",
     "configs = load_sagemaker_config()\n",
     "\n",
     "session = sagemaker.Session()\n",
     "role = sagemaker.get_execution_role()\n",
     "\n",
+    "\n",
     "print(f\"Execution Role: {role}\")\n",
     "print(f\"Default S3 Bucket: {bucket_name}\")"
    ]
@@ -130,11 +129,14 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "inference_image_uri = sagemaker.image_uris.retrieve(\n",
-    "    framework=\"djl-lmi\", \n",
-    "    region=session.boto_session.region_name, \n",
-    "    version=\"0.29.0\"\n",
-    ")\n",
+    "# commenting until LMI 0.33.0 available via SageMaker SDK\n",
+    "# inference_image_uri = sagemaker.image_uris.retrieve(\n",
+    "#     framework=\"djl-lmi\", \n",
+    "#     region=session.boto_session.region_name, \n",
+    "#     version=\"0.33.0\"\n",
+    "# )\n",
+    "\n",
+    "inference_image_uri = f\"763104351884.dkr.ecr.{region}.amazonaws.com/djl-inference:0.33.0-lmi15.0.0-cu128\"\n",
     "pretty_print_html(f\"using image to host: {inference_image_uri}\")"
    ]
   },
@@ -153,7 +155,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "model_id = \"deepseek-ai/DeepSeek-R1-Distill-Llama-8B\"\n",
+    "model_id = \"Qwen/Qwen3-4B-Instruct-2507\"\n",
     "model_id_filesafe = model_id.replace(\"/\",\"_\")\n",
     "\n",
     "use_local_model = True #set to false for the training job to download from HF, otherwise True will download locally"
@@ -225,7 +227,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "model_name = \"DeepSeek-R1-Distill-Llama-8B\"\n",
+    "model_name = \"Qwen3-4B-Instruct-2507\"\n",
     "\n",
     "lmi_model = sagemaker.Model(\n",
     "    image_uri=inference_image_uri,\n",
@@ -242,12 +244,15 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "base_endpoint_name = f\"{model_name}-endpoint\"\n",
+    "from sagemaker.utils import name_from_base\n",
+    "\n",
+    "endpoint_name = f\"{model_name}-endpoint\"\n",
+    "BASE_ENDPOINT_NAME = name_from_base(endpoint_name)\n",
     "\n",
     "predictor = lmi_model.deploy(\n",
     "    initial_instance_count=1, \n",
     "    instance_type=\"ml.g5.2xlarge\",\n",
-    "    endpoint_name=base_endpoint_name\n",
+    "    endpoint_name=BASE_ENDPOINT_NAME\n",
     ")"
    ]
   },
@@ -258,30 +263,19 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "base_prompt = f\"\"\"\n",
-    "<|begin_of_text|>\n",
-    "<|start_header_id|>system<|end_header_id|>\n",
-    "You are a medical expert with advanced knowledge in clinical reasoning, diagnostics, and treatment planning. \n",
+    "SYSTEM_PROMPT = f\"\"\"You are a medical expert with advanced knowledge in clinical reasoning, diagnostics, and treatment planning. \n",
     "Below is an instruction that describes a task, paired with an input that provides further context. \n",
     "Write a response that appropriately completes the request.\n",
-    "Before answering, think carefully about the question and create a step-by-step chain of thoughts to ensure a logical and accurate response.\n",
-    "<|eot_id|><|start_header_id|>user<|end_header_id|>\n",
-    "{{question}}<|eot_id|>\n",
-    "<|start_header_id|>assistant<|end_header_id|>\"\"\""
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "6b37e7f1-730c-4b31-aa3b-55e2009f8f04",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "prompt = base_prompt.format(\n",
-    "    question=\"A 3-week-old child has been diagnosed with late onset perinatal meningitis, and the CSF culture shows gram-positive bacilli. What characteristic of this bacterium can specifically differentiate it from other bacterial agents?\"\n",
-    ")\n",
+    "Before answering, think carefully about the question and create a step-by-step chain of thoughts to ensure a logical and accurate response.\"\"\"\n",
+    "\n",
+    "USER_PROMPT = \"A 3-week-old child has been diagnosed with late onset perinatal meningitis, and the CSF culture shows gram-positive bacilli. What characteristic of this bacterium can specifically differentiate it from other bacterial agents?\"\n",
     "\n",
-    "print(prompt)"
+    "messages = [\n",
+    "    {\"role\": \"system\", \"content\": SYSTEM_PROMPT},\n",
+    "    {\"role\": \"user\", \"content\": USER_PROMPT},\n",
+    "]\n",
+    "\n",
+    "messages"
    ]
   },
   {
@@ -292,35 +286,44 @@
    "outputs": [],
    "source": [
     "predictor = sagemaker.Predictor(\n",
-    "    endpoint_name=base_endpoint_name,\n",
+    "    endpoint_name=BASE_ENDPOINT_NAME,\n",
     "    sagemaker_session=sagemaker_session,\n",
     "    serializer=sagemaker.serializers.JSONSerializer(),\n",
     "    deserializer=sagemaker.deserializers.JSONDeserializer(),\n",
     ")\n",
     "\n",
     "response = predictor.predict({\n",
-    "\t\"inputs\": prompt,\n",
+    "\t\"messages\": messages,\n",
     "    \"parameters\": {\n",
     "        \"temperature\": 0.2,\n",
     "        \"top_p\": 0.9,\n",
     "        \"return_full_text\": False,\n",
-    "        \"max_new_tokens\": 1024,\n",
-    "        \"stop\": ['<|eot_id|>']\n",
+    "        \"max_new_tokens\": 1024\n",
     "    }\n",
     "})\n",
     "\n",
-    "response = response[\"generated_text\"].split(\"<|eot_id|>\")[0]\n",
+    "response[\"choices\"][0][\"message\"][\"content\"]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "165c8660-ee18-411f-9d8a-8032c6171d77",
+   "metadata": {},
+   "source": [
+    "### Store variables\n",
     "\n",
-    "response"
+    "Save the endpoint name for use later"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "dbfc37bb-dc1f-4ba7-9948-6e482c1c86b0",
+   "id": "0ed6ca9e-705c-4d01-9118-110b86caaef6",
    "metadata": {},
    "outputs": [],
-   "source": []
+   "source": [
+    "%store BASE_ENDPOINT_NAME"
+   ]
   }
  ],
  "metadata": {

workshops/fine-tuning-with-sagemakerai-and-bedrock/task_01_foundation_model_playground/scripts/requirements.txt

@@ -1,16 +1,16 @@
-transformers==4.48.2
+transformers==4.53.0
 peft==0.14.0
 accelerate==1.3.0
 bitsandbytes==0.45.1
 datasets==3.2.0
 evaluate==0.4.3
 huggingface_hub[hf_transfer]==0.33.4
-mlflow
+mlflow==2.22.2
 safetensors>=0.4.5
-sagemaker==2.239.0
+sagemaker==2.252.0
 sagemaker-mlflow==0.1.0
 sentencepiece==0.2.0
 scikit-learn==1.6.1
 tokenizers>=0.21.0
 trl==0.9.6
-py7zr
+py7zr==1.0.0