Teknium
c49fa88b80
* refactor(skills): shipped-set slim — 15 skills to optional, github six-way merge, pdf absorbs OCR+nano-pdf, channel-gated teams pipeline
Maintainer-directed shipped-skills curation (skills index 1,900 -> ~1,400
tok/call on desktop; every session pays the index, so this is a per-call
diet on all installs):
- optional-skills moves (installable via skills hub, history preserved):
creative comfyui/ascii-art/excalidraw/pretext/sketch/touchdesigner-mcp;
ALL of mlops (huggingface-hub, llama-cpp, serving-llms-vllm,
weights-and-biases, evaluating-llms-harness — subcategory structure
kept); research-paper-writing (55 supporting files, 17.3K-tok load);
openhue; blogwatcher (first taught the cronjob monitor-field watch
pattern + web_extract instead of pre-cron manual workflows)
- DELETED session-librarian (Aug-12 'inspired by Perplexity Computer'
port, never maintainer-intended; session_search covers discovery)
- github: six skills (auth, issues, pr-workflow, issue-to-pr,
code-review, repo-management) merged into ONE software-development/
github skill — routing body + complete per-workflow references;
benbarclay authorship credited; codebase-inspection rides along;
discipline pins from test_github_issue_to_pr_skill.py preserved
against the reference body in the new test_github_skill.py
- pdf absorbs ocr-and-documents + nano-pdf as references/ + scripts
(extract_pymupdf, extract_marker converted to the argparse house
standard its contract test enforces)
- NEW session_platforms frontmatter gate (metadata.hermes): hides a
skill from the index on gateway channels it is not for; fail-open on
unknown platform; teams-meeting-pipeline gated to [teams, cron]
- blocked-page-recovery: research -> new web category; trigger-first
description ('Use when a fetch fails: 403/429, paywall, WAF, bot
wall.') so the model actually reaches for it on blocked fetches
- docs regenerated via generate-skill-docs.py (195 pages); related_skills
swept repo-wide; tests: 1672 passed (2 openclaw failures pre-existing
on clean main, Windows-local)
* chore: ignore .skills_prompt_snapshot.json (local index cache, accidentally committed)
3.1 KiB
title, sidebar_label, description
| title | sidebar_label | description |
|---|---|---|
| Pytorch Fsdp — Fully sharded data-parallel training for large models | Pytorch Fsdp | Fully sharded data-parallel training for large models |
{/* This page is auto-generated from the skill's SKILL.md by website/scripts/generate-skill-docs.py. Edit the source SKILL.md, not this page. */}
Pytorch Fsdp
Fully sharded data-parallel training for large models.
Skill metadata
| 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
:::info The following is the complete skill definition that Hermes loads when this skill is triggered. This is what the agent sees as instructions when the skill is active. :::
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 read_file 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 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
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:
- Re-run the scraper with the same configuration
- The skill will be rebuilt with the latest information