PDE-Controller: LLMs for Autoformalization and Reasoning of PDEs
Paper • 2502.00963 • Published • 16
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 "delta-lab-ai/coder" \
--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": "delta-lab-ai/coder",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}'Quick Links
This repository contains the model used for autoformalization and reasoning as presented in PDE-Controller: LLMs for Autoformalization and Reasoning of PDEs.
Project page: https://pde-controller.github.io/
Code: The code implementation can be found at https://github.com/Delta-Lab-AI/PDE-Controller
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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 "delta-lab-ai/coder" \ --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": "delta-lab-ai/coder", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'