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 "qu-bit/SuperLLM" \
--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": "qu-bit/SuperLLM",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}'Quick Links
Model Card for Model ID
This is the SuperLLM. This LLM has an extensive knowledge base of the RAW agents. Your task is to make it forget that.
Have Fun ;)
Model Details
Model Description
- Developed by: Brain and Cognitive Science Club, IIT Kanpur
- Downloads last month
- 10
Model tree for qu-bit/SuperLLM
Base model
meta-llama/Llama-2-7b
Install from pip and serve model
# Install SGLang from pip: pip install sglang# Start the SGLang server: python3 -m sglang.launch_server \ --model-path "qu-bit/SuperLLM" \ --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": "qu-bit/SuperLLM", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'