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 "BigSalmon/InstructGPT2Large" \
--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": "BigSalmon/InstructGPT2Large",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}'Quick Links
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
Example prompts
Below is an instruction that describes a task. Write a response that appropriately completes the request.
### Instruction:
List five advantages of using solar energy.
### Response:
1. Solar energy is renewable and sustainable.
2. Low ongoing costs and no fuel expenses.
3. Generates no pollution or noise.
4. Easily scalable for different types of applications.
5. Solar energy is widely available in most regions.
Below is an instruction that describes a task. Write a response that appropriately completes the request.
### Instruction:
Generate an example of a travel destination in your favorite country.
### Response:
My favorite travel destination in Australia is Fraser Island, located on the eastern coast.
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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 "BigSalmon/InstructGPT2Large" \ --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": "BigSalmon/InstructGPT2Large", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'