claude

distributed-training

Distributed training: DDP, FSDP, DeepSpeed ZeRO, model parallelism, mixed precision, and multi-node debugging.

0 on GitHubby Diego Bodartv1.0.0MITupdated 1 month ago
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Plugin distributed-training from marketplace libre-mlops in HermeticOrmus/LibreMLOps-Claude-Code. Commands read from the repo's manifest — 1 month ago.

What it installs

Skills (1)

  • distributed-training-patterns

    Distributed training patterns with code: a PyTorch DDP loop, FSDP with a transformer auto-wrap policy, DeepSpeed ZeRO-3 configuration, AMP with GradScaler, gradient checkpointing, and data loading across ranks. Use when scaling training past one GPU.

Slash commands (1)

  • /distributed-training:dist-train

    Generate DDP, FSDP, or DeepSpeed configuration, write torchrun or SLURM launch commands, read training metrics, or debug out-of-memory errors and NCCL timeouts.

Subagents (1)

  • distributed-training-engineer

    Use this agent when training has to span several GPUs or nodes, or a multi-GPU job hits out-of-memory errors, NCCL timeouts, or instability. It chooses and configures DDP, FSDP, DeepSpeed ZeRO, or Megatron-LM parallelism and mixed precision, and states the speed, memory, and cost trade-offs.

View source on GitHub

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