| set -euo pipefail | |
| PROJECT_DIR="${PROJECT_DIR:-/workspace/KAWK50M}" | |
| VENV_DIR="${VENV_DIR:-${PROJECT_DIR}/.venv}" | |
| if [[ ! -d "${PROJECT_DIR}" ]]; then | |
| echo "Project directory not found: ${PROJECT_DIR}" >&2 | |
| exit 1 | |
| fi | |
| cd "${PROJECT_DIR}" | |
| if [[ ! -x "${VENV_DIR}/bin/python" ]]; then | |
| python -m venv --system-site-packages "${VENV_DIR}" | |
| fi | |
| # Keep the CUDA-enabled PyTorch bundled with the RunPod image available while | |
| # installing this project into an isolated environment (PEP 668 compatible). | |
| source "${VENV_DIR}/bin/activate" | |
| python -m pip install --upgrade pip | |
| python -m pip install -e . | |
| mkdir -p data/raw data/clean data/tokenized artifacts runs | |
| nvidia-smi | |
| python -m scripts.model_info --config configs/model_50m.yaml | |
| echo | |
| echo "Bootstrap complete." | |
| echo "Virtual environment: ${VENV_DIR}" | |
| echo "After tokenizer and token binaries are present, run:" | |
| echo " bash runpod/train_5090.sh" | |