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 "TeeZee/Orca-2-13b_flat" \
--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": "TeeZee/Orca-2-13b_flat",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}'Quick Links
Lots of good models use Orca for their merges, however vanilla Orca has vocabulary size of 32003, 3 last tokens are ChatML tokens and a PAD token. This causes errors during a merge with models with standard 32000 vocabulary size.
I've removed those tokens from volabulary and resized model embeddings to mach 32000 standard size. So this model is ready to be used as a merge component in mergekit. It may not work on its own with ChatML template anymore.
model.resize_token_embeddings(32000)
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Install from pip and serve model
# Install SGLang from pip: pip install sglang# Start the SGLang server: python3 -m sglang.launch_server \ --model-path "TeeZee/Orca-2-13b_flat" \ --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": "TeeZee/Orca-2-13b_flat", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'