Instructions to use my-ai-stack/Stack-2-9-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use my-ai-stack/Stack-2-9-finetuned with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="my-ai-stack/Stack-2-9-finetuned")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("my-ai-stack/Stack-2-9-finetuned")
model = AutoModelForCausalLM.from_pretrained("my-ai-stack/Stack-2-9-finetuned")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use my-ai-stack/Stack-2-9-finetuned with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "my-ai-stack/Stack-2-9-finetuned"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "my-ai-stack/Stack-2-9-finetuned",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/my-ai-stack/Stack-2-9-finetuned

SGLang

How to use my-ai-stack/Stack-2-9-finetuned with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "my-ai-stack/Stack-2-9-finetuned" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "my-ai-stack/Stack-2-9-finetuned",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "my-ai-stack/Stack-2-9-finetuned" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "my-ai-stack/Stack-2-9-finetuned",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use my-ai-stack/Stack-2-9-finetuned with Docker Model Runner:
```
docker model run hf.co/my-ai-stack/Stack-2-9-finetuned
```

walidsobhie-code Claude Opus 4.6 commited on Apr 10

Commit

87ed83d

1 Parent(s): a075b90

fix: improve Kaggle notebook training

Browse files

- Fix training command for better output
- Add clear variable placeholders

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

Files changed (1) hide show

notebooks/kaggle_128k_training.ipynb +10 -32

notebooks/kaggle_128k_training.ipynb CHANGED Viewed

@@ -43,14 +43,7 @@
    "execution_count": null,
    "metadata": {},
    "outputs": [],
-   "source": [
-    "import os\n",
-    "from huggingface_hub import login\n",
-    "\n",
-    "# Add HF_TOKEN to Kaggle Secrets: https://www.kaggle.com/docs/secrets\n",
-    "HF_TOKEN = \"YOUR_HF_TOKEN\"  # ← Replace with your token (or use Kaggle Secrets)\n",
-    "login(token=HF_TOKEN)"
-   ]
   },
   {
    "cell_type": "markdown",
@@ -64,27 +57,7 @@
    "execution_count": null,
    "metadata": {},
    "outputs": [],
-   "source": [
-    "import subprocess, os\n",
-    "os.chdir(\"/kaggle/working/stack-2.9\")\n",
-    "\n",
-    "env = dict(os.environ, HF_TOKEN=HF_TOKEN)\n",
-    "\n",
-    "result = subprocess.run([\n",
-    "    \"python3\", \"training/train_extended_context.py\",\n",
-    "    \"--model-path\", \"Qwen/Qwen2.5-Coder-1.5B\",\n",
-    "    \"--data-path\", \"training/training-data/tool_examples_combined.jsonl\",\n",
-    "    \"--output-dir\", \"/kaggle/working/stack-2.9-128k\",\n",
-    "    \"--context-length\", \"131072\",\n",
-    "    \"--lora-rank\", \"64\",\n",
-    "    \"--epochs\", \"3\",\n",
-    "    \"--push-to-hub\",\n",
-    "    \"--hub-model-id\", \"YOUR_USERNAME/stack-2.9-128k\"  # ← Replace with your username\n",
-    "], env=env, capture_output=True, text=True)\n",
-    "\n",
-    "print(\"STDOUT:\", result.stdout[-5000:] if result.stdout else \"None\")\n",
-    "print(\"STDERR:\", result.stderr[-2000:] if result.stderr else \"None\")"
-   ]
   },
   {
    "cell_type": "markdown",
@@ -109,8 +82,13 @@
    "accelerator": "GPU",
    "dataSources": [],
    "dockerImageVersion": "gpu",
-   "gpuRequirements": { "top": "p100" },
-   "kernelImage": { "id": "docker", "name": "docker" }
   },
   "kernelspec": {
    "display_name": "Python 3",
@@ -124,4 +102,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 4
-}

    "execution_count": null,
    "metadata": {},
    "outputs": [],
+   "source": "import os\nfrom huggingface_hub import login\n\n# Replace with your actual HF token\nHF_TOKEN = \"YOUR_HF_TOKEN\"  # ← Replace with your token\nlogin(token=HF_TOKEN)\nprint(\"✓ Logged in to HuggingFace\")"
   },
   {
    "cell_type": "markdown",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
+   "source": "import os\nos.chdir(\"/kaggle/working/stack-2.9\")\n\n# Training parameters - UPDATE THESE\nYOUR_HF_TOKEN = \"YOUR_HF_TOKEN\"  # ← Replace with your HF token\nYOUR_USERNAME = \"your-username\"  # ← Replace with your HF username\n\n# Run training\n!python training/train_extended_context.py \\\n    --model-path Qwen/Qwen2.5-Coder-1.5B \\\n    --data-path training/training-data/tool_examples_combined.jsonl \\\n    --output-dir /kaggle/working/stack-2.9-128k \\\n    --context-length 131072 \\\n    --lora-rank 64 \\\n    --epochs 3 \\\n    --batch-size 1 \\\n    --grad-accum 16 \\\n    --push-to-hub \\\n    --hub-model-id {YOUR_USERNAME}/stack-2.9-128k"
   },
   {
    "cell_type": "markdown",
    "accelerator": "GPU",
    "dataSources": [],
    "dockerImageVersion": "gpu",
+   "gpuRequirements": {
+    "top": "p100"
+   },
+   "kernelImage": {
+    "id": "docker",
+    "name": "docker"
+   }
   },
   "kernelspec": {
    "display_name": "Python 3",
  },
  "nbformat": 4,
  "nbformat_minor": 4
+}