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

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 4

Commit

389f026

1 Parent(s): a9f935e

fix: use different base path to avoid nested directory issue

Browse files

- Change BASE_PATH from stack-2.9 to stack-2.9-colab
- This prevents any cached nested directories

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

Files changed (1) hide show

colab_train_stack29.ipynb +1 -14

colab_train_stack29.ipynb CHANGED Viewed

@@ -52,20 +52,7 @@
    "execution_count": null,
    "metadata": {},
    "outputs": [],
-   "source": [
-    "from google.colab import drive\n",
-    "drive.mount('/content/drive')\n",
-    "\n",
-    "# Set up paths on Drive - ALL OUTPUT GOES HERE\n",
-    "import os\n",
-    "BASE_PATH = \"/content/drive/MyDrive/stack-2.9\"\n",
-    "os.makedirs(BASE_PATH, exist_ok=True)\n",
-    "os.chdir(BASE_PATH)\n",
-    "print(f\"\\n✅ Working directory: {os.getcwd()}\")\n",
-    "print(f\"All outputs will be saved to: {BASE_PATH}\")\n",
-    "print(\"\\nCurrent folder contents:\")\n",
-    "!ls -la"
-   ]
   },
   {
    "cell_type": "markdown",

    "execution_count": null,
    "metadata": {},
    "outputs": [],
+   "source": "from google.colab import drive\ndrive.mount('/content/drive')\n\n# Set up paths on Drive - ALL OUTPUT GOES HERE\nimport os\nBASE_PATH = \"/content/drive/MyDrive/stack-2.9-colab\"\nos.makedirs(BASE_PATH, exist_ok=True)\nos.chdir(BASE_PATH)\nprint(f\"\\n✅ Working directory: {os.getcwd()}\")\nprint(f\"All outputs will be saved to: {BASE_PATH}\")\nprint(\"\\nCurrent folder contents:\")\n!ls -la"
   },
   {
    "cell_type": "markdown",