微调保存时，8张显卡的结果都保存结果需要很大存储空间，是否可以在一张显卡中保存
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Description
finetune_moss.py
if global_step % args.save_step == 0 and torch.cuda.current_device() == 0:
model.save_checkpoint(args.output_dir, global_step)
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Research direction
Start in finetune_moss.py at the save_step condition and inspect how checkpoint saving behaves across the eight-GPU distributed run. Trace model.save_checkpoint and the output directory to determine why multiple GPU results consume storage. Done means a checkpoint is written once by the intended GPU without losing the expected training state.
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Assessment
- Tech stack
- python, pytorch
- Domain
- distributed-systems, machine-learning
- Issue type
- Feature
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100