Agent skill · software engineering · nousresearch
pytorch-fsdp
Fully sharded data-parallel training for large models.
Why this skill is useful
Provides specific patterns and best practices for implementing fully sharded data-parallel training with PyTorch that are not widely known.
What it needs
Requires torch, transformers installed locally. About 1k tokens when loaded. Last updated 2026-08-07. 226,679 stars on the source repository.
What this skill does
Pytorch-Fsdp Skill Assistance with pytorch-fsdp development, generated from official documentation. When to Use This Skill This skill should be triggered when: Working with pytorch-fsdp Asking about pytorch-fsdp features or APIs Implementing pytorch-fsdp solutions Debugging pytorch-fsdp code Learning pytorch-fsdp best practices Quick Reference The full common-patterns catalog (~157k chars of runnable FSDP snippets) lives in references/common-patterns.md — load it with readfile when you need wrapping, sharding-strategy, checkpoint, or mixed-precision examples. Start there rather than reconstructing FSDP incantations from memory. Reference Files This skill includes comprehensive documentation in references/: other.md - Other documentation Use view to read specific reference files when detailed information is needed. Working with This Skill For Beginners Start with the gettingstarted or tutorials reference files for foundational concepts. For Specific Features Use the appropriate category reference file (api, guides, etc.) for detailed information. For Code Examples The quick reference section above contains common patterns extracted from the official docs. Resources references/ Organized documentation extracted from official sources. These files contain: Detailed explanations Code examples with language annotations Links to original documentation Table of contents for quick navigation scripts/ Add helper scripts here for common automation tasks. assets/ Add templates, boilerplate, or example projects here. Notes This skill was automatically generated from official documentation Reference files preserve the structure and examples from source docs Code examples include language detection for better syntax highlighting Quick reference patterns are extracted from common usage examples in the docs Updating To refresh this skill with updated documentation: 1. Re-run the scraper with the same configuration 2. The skill will be rebuilt with the latest information
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills nousresearch/pytorch-fsdp