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 "LLM-course/chess_minfreq2" \
--host 0.0.0.0 \
--port 30000# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "LLM-course/chess_minfreq2",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}'Quick Links
chess_minfreq2
Chess model submitted to the LLM Course Chess Challenge.
Submission Info
- Submitted by: alexandreduplessis
- Parameters: 3,030,912
- Organization: LLM-course
Model Details
- Architecture: Chess Transformer (GPT-style)
- Vocab size: 18253
- Embedding dim: 128
- Layers: 4
- Heads: 4
- Downloads last month
- 1
Install from pip and serve model
# Install SGLang from pip: pip install sglang# Start the SGLang server: python3 -m sglang.launch_server \ --model-path "LLM-course/chess_minfreq2" \ --host 0.0.0.0 \ --port 30000# Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "LLM-course/chess_minfreq2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'