How to use from
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 "Undi95/CodeEngine" \
    --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": "Undi95/CodeEngine",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'
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 "Undi95/CodeEngine" \
        --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": "Undi95/CodeEngine",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'
Quick Links

model: https://huggingface.co/jondurbin/airoboros-l2-13b-2.1 + lora: https://huggingface.co/jondurbin/airoboros-lmoe-13b-2.1/tree/main/adapters/code

For Dampf.

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric Value
Avg. 50.96
ARC (25-shot) 58.36
HellaSwag (10-shot) 82.27
MMLU (5-shot) 54.18
TruthfulQA (0-shot) 45.18
Winogrande (5-shot) 74.59
GSM8K (5-shot) 1.52
DROP (3-shot) 40.59
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