distributed-training

Use when training models across multiple GPUs or nodes, handling large models that don't fit in memory, or optimizing training throughput — covers DDP, FSDP, DeepSpeed ZeRO, model/data parallelism, and gradient checkpointingUse when ", " mentioned.