Instructions to use cyankiwi/North-Mini-Code-1.0-AWQ-INT4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use cyankiwi/North-Mini-Code-1.0-AWQ-INT4 with Transformers:

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

pipe = pipeline("text-generation", model="cyankiwi/North-Mini-Code-1.0-AWQ-INT4")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("cyankiwi/North-Mini-Code-1.0-AWQ-INT4")
model = AutoModelForCausalLM.from_pretrained("cyankiwi/North-Mini-Code-1.0-AWQ-INT4")
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 cyankiwi/North-Mini-Code-1.0-AWQ-INT4 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "cyankiwi/North-Mini-Code-1.0-AWQ-INT4"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "cyankiwi/North-Mini-Code-1.0-AWQ-INT4",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/cyankiwi/North-Mini-Code-1.0-AWQ-INT4

SGLang

How to use cyankiwi/North-Mini-Code-1.0-AWQ-INT4 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 "cyankiwi/North-Mini-Code-1.0-AWQ-INT4" \
    --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": "cyankiwi/North-Mini-Code-1.0-AWQ-INT4",
		"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 "cyankiwi/North-Mini-Code-1.0-AWQ-INT4" \
        --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": "cyankiwi/North-Mini-Code-1.0-AWQ-INT4",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use cyankiwi/North-Mini-Code-1.0-AWQ-INT4 with Docker Model Runner:
```
docker model run hf.co/cyankiwi/North-Mini-Code-1.0-AWQ-INT4
```

probably an issue with vllm 0.23.0

by saadsafi - opened 23 days ago

Discussion

saadsafi

23 days ago

File ".venv/lib/python3.12/site-packages/vllm/model_executor/model_loader/default_loader.py", line 286, in
(Worker_PP1 pid=6625) ERROR 06-13 13:42:00 [multiproc_executor.py:888] return ((source.prefix + name, tensor) for (name, tensor) in weights_iterator)
(Worker_PP1 pid=6625) ERROR 06-13 13:42:00 [multiproc_executor.py:888] ^^^^^^^^^^^^^^^^
(Worker_PP1 pid=6625) ERROR 06-13 13:42:00 [multiproc_executor.py:888] File ".venv/lib/python3.12/site-packages/vllm/model_executor/model_loader/weight_utils.py", line 1026, in safetensors_weights_iterator
(Worker_PP1 pid=6625) ERROR 06-13 13:42:00 [multiproc_executor.py:888] param = f.get_tensor(name)
(Worker_PP1 pid=6625) ERROR 06-13 13:42:00 [multiproc_executor.py:888] ^^^^^^^^^^^^^^^^^^
(Worker_PP1 pid=6625) ERROR 06-13 13:42:00 [multiproc_executor.py:888] ValueError: could not determine the shape of object type 'torch.storage.UntypedStorage'
(EngineCore pid=6613) ERROR 06-13 13:42:02 [core.py:1195] EngineCore failed to start.

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