Instructions to use North-ML1/Wind-Edge-1.6-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use North-ML1/Wind-Edge-1.6-Base with Transformers:

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

pipe = pipeline("text-generation", model="North-ML1/Wind-Edge-1.6-Base", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("North-ML1/Wind-Edge-1.6-Base", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use North-ML1/Wind-Edge-1.6-Base with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "North-ML1/Wind-Edge-1.6-Base"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "North-ML1/Wind-Edge-1.6-Base",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/North-ML1/Wind-Edge-1.6-Base

SGLang

How to use North-ML1/Wind-Edge-1.6-Base 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 "North-ML1/Wind-Edge-1.6-Base" \
    --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": "North-ML1/Wind-Edge-1.6-Base",
		"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 "North-ML1/Wind-Edge-1.6-Base" \
        --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": "North-ML1/Wind-Edge-1.6-Base",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use North-ML1/Wind-Edge-1.6-Base with Docker Model Runner:
```
docker model run hf.co/North-ML1/Wind-Edge-1.6-Base
```

Sweet model!

by Datdanboi25 - opened about 15 hours ago

Discussion

Datdanboi25

about 15 hours ago

Awesome model man!
Any chance we could get some benchmarks?
Keep up the good work!

arthu1

North ML org about 2 hours ago

First comment thanks!
I built this at 11 with a little of Modal credits, but if you want, benchmark then pr the gguf model on F16, temp 0 and stuff.
It won't go high (not in my testing it didn't.) but yeah!
Thanks!

Datdanboi25

about 2 hours ago

Haha no worries, Keep up the good work!

arthu1

North ML org about 2 hours ago

thanks! can you benchmark it tho?
just asking?

Arthur

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