Results for “fully-sharded-data-parallel”

Adds PyTorch FSDP2 (fully_shard) to training scripts with correct init, sharding, mixed precision/offload config, and distributed checkpointing. Use when models exceed single-GPU memory or when you need DTensor-based sharding with DeviceMesh.

Adds PyTorch FSDP2 (fully_shard) to training scripts with correct init, sharding, mixed precision/offload config, and distributed checkpointing. Use when models exceed single-GPU memory or when you need DTensor-based sharding with DeviceMesh.

Adds PyTorch FSDP2 (fully_shard) to training scripts with correct init, sharding, mixed precision/offload config, and distributed checkpointing. Use when models exceed single-GPU memory or when you need DTensor-based sharding with DeviceMesh.

Consolidates 89 high-integrity SOPs for the Full department of the Galyarder Framework, covering adapter creation, execution protocols, and multi-agent hygiene.

GPU-safe parallel processing patterns for KINTSUGI to prevent OOM crashes and ensure Jupyter-compatible progress output

Apache Spark, Hadoop, distributed computing, and large-scale data processing for petabyte-scale workloads

Orchestrate parallel scientist agents for comprehensive analysis with AUTO mode