Instructions to use cosmicstack/cosmic-lightning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use cosmicstack/cosmic-lightning with Transformers:

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

pipe = pipeline("text-generation", model="cosmicstack/cosmic-lightning", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("cosmicstack/cosmic-lightning", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use cosmicstack/cosmic-lightning with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/cosmicstack/cosmic-lightning

SGLang

How to use cosmicstack/cosmic-lightning 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 "cosmicstack/cosmic-lightning" \
    --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": "cosmicstack/cosmic-lightning",
		"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 "cosmicstack/cosmic-lightning" \
        --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": "cosmicstack/cosmic-lightning",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use cosmicstack/cosmic-lightning with Docker Model Runner:
```
docker model run hf.co/cosmicstack/cosmic-lightning
```

Model appears to be unmodified LFM3-1.7B

by darrowoflykos - opened about 9 hours ago

Discussion

darrowoflykos

about 9 hours ago

I'm not seeing any differences here between this model and LFM3-1.7B. It even has lfm3 in the model tags. This is a violation of the LFM Open License v1.0, which requires that you provide a copy of their license with your redistribution, along with other requirements. Also, the model card, at least to my eyes given the environmental impact report and citation request, seems to imply that this is an original model which you've trained, which I don't believe is correct

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