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Agent skill

Torch Pipeline Parallelism

by lazyFrogLOL in lazyFrogLOL/Harness_Engineering

This skill provides guidance for implementing PyTorch pipeline parallelism for distributed training of large language models.

No licenceAuto-check passedAI & LLM Engineering

Install Torch Pipeline Parallelism

skills CLI
$ npx skills add lazyFrogLOL/Harness_Engineering --skill torch-pipeline-parallelism -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install lazyFrogLOL/Harness_Engineering torch-pipeline-parallelism --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/lazyFrogLOL/Harness_Engineering.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/torch-pipeline-parallelism .claude/skills/torch-pipeline-parallelism && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
torch-pipeline-parallelism
GitHub stars
128
Token cost
~2.1k tokens
SKILL.md length
658 words
Files
1
Skills in repo
32
Repo updated
First seen
Licence
None found

At a glance

This skill provides guidance for implementing PyTorch pipeline parallelism for distributed training of large language models.

  • Works in 12 steps: Model Analysis and Planning → Implement Core Functions → Communication Implementation → …
  • Tasks that involve Deep learning
  • SKILL.md covers Overview, Key Concepts, Implementation Approach and Verification Strategy, plus 2 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Torch Pipeline Parallelism is an agent skill from lazyFrogLOL/Harness_Engineering. This skill provides guidance for implementing PyTorch pipeline parallelism for distributed training of large language models. It should be used when implementing pipeline parallel training loops, partitioning transformer models across GPUs, or working with AFAB (All-Forward-All-Backward) scheduling patterns. The skill covers model partitioning, inter-rank communication, gradient flow management, and common pitfalls in distributed training implementations.

Its SKILL.md is about 2.1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in AI & LLM Engineering, covering Deep learning. It works with PyTorch.

When your agent uses it

  • Tasks that involve Deep learning

Example prompts

  • “/torch-pipeline-parallelism”

Requirements

  • Python 3

Workflow steps

12 steps, taken from the step headings in SKILL.md.

  1. Model Analysis and Planning
  2. Implement Core Functions
  3. Communication Implementation
  4. Gradient Flow Management
  5. Truncated File Writes
  6. Position Embedding Mishandling
  7. Incorrect Loss Scaling
  8. Communication Deadlocks
  9. Broken Gradient Graph
  10. Architecture Assumptions
  11. Dtype and Device Mismatches
  12. Missing Return Values

What it can do on your machine

Read from SKILL.md and the folder at commit cae3b25. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are python).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Torch Pipeline Parallelism loads about 2.1k tokens when it runs. Until then it costs about 122 tokens; SKILL.md has 658 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~122
When it runs · the whole SKILL.md, loaded when a task matches
~2.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

Without a licence we can't republish the file, so here is its outline and opening line. It has 658 words (~2,098 tokens).

“Pipeline parallelism distributes model layers across multiple GPUs/ranks, enabling training of models too large for a single device. This skill provides procedural guidance for implementing pipeline parallel training with proper model partitioning, communication patterns, and gradient handling.”

— opening of SKILL.md by lazyFrogLOL
name
torch-pipeline-parallelism

Read the full SKILL.md on GitHub

Files

Just SKILL.md in skills/torch-pipeline-parallelism of lazyFrogLOL/Harness_Engineering.

Open the folder on GitHubat commit cae3b25

Compare with similar skills

Torch Pipeline Parallelism next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Torch Pipeline Parallelism compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Torch Pipeline Parallelism this skilllazyFrogLOL/Harness_Engineering128—~2.1kAutomated safety check: PassNone
Add Uint Supportpytorch/pytorch104k2 repos~2.3kAutomated safety check: PassCustom licence
CLIP Image-Text MatchingOrchestra-Research/AI-Research-SKILLs13k7 repos~1.7kAutomated safety check: PassMIT
Add Torch Shapes Examplefacebook/pyrefly7.1k—~1.3kAutomated safety check: PassMIT
Ghstack CIpytorch/pytorch104k—~1.4kAutomated safety check: PassCustom licence
MUSA GPU Training Optimizeropen-infra-skills/infra-skills141—~1.7kAutomated safety check: PassApache-2.0

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Works with

Categories

Questions about Torch Pipeline Parallelism

What does Torch Pipeline Parallelism do?

This skill provides guidance for implementing PyTorch pipeline parallelism for distributed training of large language models. Torch Pipeline Parallelism is an agent skill from lazyFrogLOL/Harness_Engineering. This skill provides guidance for implementing PyTorch pipeline parallelism for distributed training of large language models.

When should I use Torch Pipeline Parallelism?

Torch Pipeline Parallelism fits situations like: tasks that involve Deep learning.

How do I install Torch Pipeline Parallelism in Claude Code?

Run `npx skills add lazyFrogLOL/Harness_Engineering --skill torch-pipeline-parallelism -a claude-code`. Or copy the skill folder (skills/torch-pipeline-parallelism in lazyFrogLOL/Harness_Engineering) into .claude/skills/torch-pipeline-parallelism in your project. Claude Code loads it when a task matches its description.

How do I install Torch Pipeline Parallelism in Codex?

Run `npx skills add lazyFrogLOL/Harness_Engineering --skill torch-pipeline-parallelism -a codex`. Or copy the skill folder (skills/torch-pipeline-parallelism in lazyFrogLOL/Harness_Engineering) into .agents/skills/torch-pipeline-parallelism in your project. Codex loads it when a task matches its description.

Can I use Torch Pipeline Parallelism in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add lazyFrogLOL/Harness_Engineering --skill torch-pipeline-parallelism -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/torch-pipeline-parallelism, .gemini/skills/torch-pipeline-parallelism, .github/skills/torch-pipeline-parallelism and .opencode/skills/torch-pipeline-parallelism in your project.

What does Torch Pipeline Parallelism need to run?

SKILL.md names no scripts, command-line tools or credentials: Torch Pipeline Parallelism is instructions for the agent only. Our summary lists: Python 3.

Does Torch Pipeline Parallelism access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Torch Pipeline Parallelism safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Torch Pipeline Parallelism use?

No licence was found for Torch Pipeline Parallelism or its repository. Without one, default copyright applies: ask the author before reusing or redistributing it.

How many tokens does Torch Pipeline Parallelism use?

About 2.1k tokens (SKILL.md is roughly 8.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Torch Pipeline Parallelism?

Skills that share tags, products or a category with Torch Pipeline Parallelism: Add Uint Support (pytorch/pytorch, 104k stars), CLIP Image-Text Matching (Orchestra-Research/AI-Research-SKILLs, 13k stars), Add Torch Shapes Example (facebook/pyrefly, 7.1k stars) and Ghstack CI (pytorch/pytorch, 104k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Torch Pipeline Parallelism?

lazyFrogLOL (a GitHub user) maintains it in lazyFrogLOL/Harness_Engineering, which has 128 GitHub stars. The repository holds 32 skills in this directory. The repository was last updated on May 18, 2026.

Source: lazyFrogLOL/Harness_Engineering on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.