torch-pipeline-parallelism
Guidance for implementing PyTorch pipeline parallelism for distributed model training. This skill should be used when tasks involve implementing pipeline parallelism, distributed training with model partitioning across GPUs/ranks, AFAB (All-Forward-All-Backward) scheduling, or inter-rank tensor communication using torch.distributed.
Installation and usage
Guidance for implementing PyTorch pipeline parallelism for distributed model training. This skill should be used when tasks involve implementing pipeline parallelism, distributed training with model partitioning across GPUs/ranks, AFAB (All-Forward-All-Backward) scheduling, or inter-rank tensor communication using torch.distributed.
Después de instalarlo, puedes usar este skill ejecutando el siguiente comando en tu terminal:
skills use torch-pipeline-parallelism