How to use from
SGLangUse 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 "kopens/aura-14b" \
--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": "kopens/aura-14b",
"messages": [
{
"role": "user",
"content": "What is the capital of France?"
}
]
}'Quick Links
Configuration Parsing Warning:In config.json: "quantization_config.modules_to_not_convert" must be an array
AWQ Version of https://huggingface.co/deepcogito/cogito-v1-preview-qwen-14B
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Model tree for kopens/aura-14b
Base model
Qwen/Qwen2.5-14B Finetuned
deepcogito/cogito-v1-preview-qwen-14B
Install from pip and serve model
# Install SGLang from pip: pip install sglang# Start the SGLang server: python3 -m sglang.launch_server \ --model-path "kopens/aura-14b" \ --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": "kopens/aura-14b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'