Download train/multinode.env.example from xixibuxixi/Muti3d: direct link, hf CLI and curl.
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https://huggingface.co/xixibuxixi/Muti3d/resolve/main/train/multinode.env.example
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hf download hf://xixibuxixi/Muti3d/train/multinode.env.example
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curl -L -o multinode.env.example https://huggingface.co/xixibuxixi/Muti3d/resolve/main/train/multinode.env.example
661 Bytes
| # Copy to multinode.env | |
| # Local node, rank 0. | |
| HEAD_HOST=10.0.0.1 | |
| MASTER_ADDR=10.0.0.1 | |
| MASTER_PORT=29500 | |
| # Common training shape. | |
| NNODES=2 | |
| NPROC=8 | |
| CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 | |
| # Remote node, rank 1. | |
| REMOTE_HOST=10.0.0.2 | |
| REMOTE_USER=root | |
| REMOTE_TRAIN_DIR=/public/0_DATA/2_Avatar/zhizhou_share/rcz/Muti3d/train | |
| # Prefer SSH keys. If password auth is needed, install sshpass on the head node | |
| # and set REMOTE_PASSWORD below. Keep this file private. | |
| REMOTE_PASSWORD= | |
| # Optional shared overrides. Leave empty to use _run_stage2_eval_wandb_core.sh defaults. | |
| RUN_NAME=muti3d_stage2_eval_wandb_multinode | |
| DATA_ROOT= | |
| INIT_DCP= | |
| OUTPUT_ROOT= | |
| WANDB_MODE=online | |