| # One-time setup of a GPU machine for the labs. Everything lives under /nvme/wsp-lab (about 15 GB). | |
| # From your laptop, in the project folder: | |
| # scp scripts/setup_vm.sh <host>:/tmp/ && ssh <host> bash /tmp/setup_vm.sh # about 10 minutes | |
| # bash scripts/sync_vm.sh <host> # copy the code | |
| # ssh <host> 'cd /nvme/wsp-lab/code && . scripts/env.sh && | |
| # python scripts/prepare_data.py --exp8 external/lm_understand-logs/exp8_math --out /nvme/wsp-lab/data && | |
| # python scripts/build_models.py && python scripts/build_models.py --variants configs/rebuilt.json' | |
| # It needs no root: Python, packages, the model and every cache go into /nvme/wsp-lab. | |
| set -euo pipefail | |
| LAB=${LAB:-/nvme/wsp-lab} | |
| UV=${UV:-$HOME/.local/bin/uv} | |
| export UV_PYTHON_INSTALL_DIR=$LAB/python UV_CACHE_DIR=$LAB/uv-cache HF_HOME=$LAB/hf | |
| mkdir -p "$LAB"/{models,data,runs,logs,code,nltk_data} | |
| cd "$LAB" | |
| [ -x "$UV" ] || { curl -LsSf https://astral.sh/uv/install.sh | sh; UV=$HOME/.local/bin/uv; } | |
| [ -x venv/bin/python ] || "$UV" venv --python 3.12 venv | |
| . venv/bin/activate | |
| "$UV" pip install "vllm==0.33.0" "flash-linear-attention==0.6.0" "math-verify[antlr4_13_2]==0.9.0" \ | |
| "lm-eval[ifeval]==0.4.13" datasets matplotlib scipy pandas | |
| python -c "import nltk; nltk.download('punkt_tab', download_dir='$LAB/nltk_data')" | |
| hf download Qwen/Qwen3.5-0.8B --revision 2fc06364715b967f1860aea9cf38778875588b17 \ | |
| --local-dir "$LAB/models/Qwen3.5-0.8B" | |
| python -c "import vllm, transformers, torch; print('vllm', vllm.__version__, 'transformers', transformers.__version__, | |
| 'torch', torch.__version__, 'cuda', torch.version.cuda)" | |
| echo SETUP-DONE | |