Instructions to use quelmap/Lightning-4b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use quelmap/Lightning-4b with Transformers:

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

pipe = pipeline("text-generation", model="quelmap/Lightning-4b")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("quelmap/Lightning-4b", dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use quelmap/Lightning-4b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "quelmap/Lightning-4b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "quelmap/Lightning-4b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/quelmap/Lightning-4b

SGLang

How to use quelmap/Lightning-4b 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 "quelmap/Lightning-4b" \
    --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": "quelmap/Lightning-4b",
		"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 "quelmap/Lightning-4b" \
        --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": "quelmap/Lightning-4b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use quelmap/Lightning-4b with Docker Model Runner:
```
docker model run hf.co/quelmap/Lightning-4b
```

Quants? Also question.

by IZA09 - opened Sep 17, 2025

Discussion

IZA09

Sep 17, 2025

•

edited Sep 17, 2025

could i request quants? preferably 8 or 6? id rather not run full precision if i can help it even if it would be easy. (unless you recommend it?)

Ive been looking for something to copilot my ObsidianMD setup, something to read through my logs and recall details i dont care to look for myself. Would this be useful for that purpose? i apologize if this is a dumb question, ive never used model for anything other than turn-based conversations and ive been window shopping.

shintaro-29

quelmap org Sep 18, 2025

We provide quantized models in the GGUF format.

Lightning-4b is a model specialized for database analysis. Since it can run on a laptop, it ensures high confidentiality and is ideal for cases where sending data to external LLM providers is not an option.

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