Use it when your goal in extending the agent is clear and you can limit it to the data and actions it actually needs.
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SKILLoptionalHermes Optional Skills
Pytorch Fsdp
Fully sharded data-parallel training for large models
Last registry verification2026-08-18v1.0.0Orchestra Research
What does it add to Hermes?
Fully sharded data-parallel training for large models
Pytorch Fsdp is a skill related to extending the agent. It adds a capability or workflow to Hermes. The publisher description explains the intent, while granted permissions determine what it can actually do.
This plain-language explanation is based on the publisher description. The original text remains visible for verification.
Do not add it merely to experiment when Hermes already has a simpler path, or when you cannot review its source and permissions.
Best for users who want a repeatable way of working inside Hermes.
Start with non-sensitive data and a small task whose result can be verified and reversed.
Original publisher description
Fully sharded data-parallel training for large models
Data source
This entry was indexed from Hermes Optional Skills. Our explanation interprets the type and domain without inventing a capability not present upstream.
Security review
The source is official or editorially reviewed, but you still need to review permissions and version compatibility.
Inspect, install, then test.
- 01Open the source
Match the publisher, license, and description to your need. Check the real update history.
- 02Review permissions and secrets
Never paste a secret value into this site. Use environment-variable names and grant the smallest scope.
- 03Copy setup only after review
The controls below copy text. They do not execute commands on your device.
- 04Test with a non-sensitive task
Inspect the visible tools, then exclude write or delete tools you do not need.
Review the command, then copy it.
hermes skills install pytorch-fsdpHermes Belarabi does not execute this command. Installation happens on your device and remains subject to Hermes scanning and your review.
Exactly what Hermes loads when this skill runs.
Reproduced from the official documentation. Read it before enabling the skill: this text becomes the agent's instructions.
Fully sharded data-parallel training for large models.
Skill metadata
A lookup table. Do not read it all; find the row that applies to you.
| Source | Optional — install with hermes skills install official/mlops/pytorch-fsdp |
| Path | optional-skills/mlops/pytorch-fsdp |
| Version | 1.0.0 |
| Author | Orchestra Research |
| License | MIT |
| Dependencies | torch>=2.0, transformers |
| Platforms | linux, macos |
| Tags | Distributed Training, PyTorch, FSDP, Data Parallel, Sharding, Mixed Precision, CPU Offloading, FSDP2, Large-Scale Training |
Reference: full SKILL.md
Explains the idea itself. Read it slowly; the later sections build on it.
Assistance with pytorch-fsdp development, generated from official documentation.
When to Use This Skill
Explains the idea itself. Read it slowly; the later sections build on it.
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
Explains the idea itself. Read it slowly; the later sections build on it.
The full common-patterns catalog (~157k chars of runnable FSDP snippets) lives in
references/common-patterns.md — load it with read_file when you need wrapping,
sharding-strategy, checkpoint, or mixed-precision examples. Start there rather than
reconstructing FSDP incantations from memory.
Reference Files
Explains the idea itself. Read it slowly; the later sections build on it.
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
Explains the idea itself. Read it slowly; the later sections build on it.
For Beginners
Start with the getting_started 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
Explains the idea itself. Read it slowly; the later sections build on it.
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
Explains the idea itself. Read it slowly; the later sections build on it.
- 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
Explains the idea itself. Read it slowly; the later sections build on it.
To refresh this skill with updated documentation:
- Re-run the scraper with the same configuration
- The skill will be rebuilt with the latest information