Instructions to use North-ML1/starlight-mini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use North-ML1/starlight-mini with Transformers:

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

pipe = pipeline("text-generation", model="North-ML1/starlight-mini")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("North-ML1/starlight-mini")
model = AutoModelForCausalLM.from_pretrained("North-ML1/starlight-mini", device_map="auto")
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 North-ML1/starlight-mini with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "North-ML1/starlight-mini"
# 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/starlight-mini",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/North-ML1/starlight-mini

SGLang

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

Docker Model Runner
How to use North-ML1/starlight-mini with Docker Model Runner:
```
docker model run hf.co/North-ML1/starlight-mini
```
Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

Updated Starlight Mini model card

This model is the original model created by North ML and fine-tuned from other models to provide 60-65% on the SWE-Benchmark. It will be helpful, but this is just our first one.

Model Details

Model Description

This model is the original model created by North ML and fine-tuned from other models to provide 60-65% on the SWE-Benchmark. It will be helpful, but this is just our first one. We are trying to find solutions to the coding shortage, for free, and Jesus Loves You! For God!

Developed by: arthu1 at the AI branch of North ML
Model type: Conversation / Text Generation
Language(s) (NLP): English.
License: MIT

Model Sources [optional]

Use it on: local devices.

Uses

Use it for your text generation needs. This is somewhat Claude Haiku 3.5 intelligence even though it performs worse. Haiku is 100B. This is 8B.

Downloads last month: 231

Safetensors

Model size

8B params

Tensor type

F16

Model tree for North-ML1/starlight-mini

Base model

arthu1/astrocoder-star-merge

Finetuned

(1)

this model

Quantizations

3 models

Dataset used to train North-ML1/starlight-mini

Space using North-ML1/starlight-mini 1

Collection including North-ML1/starlight-mini

Daily Drivers

Collection

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