torch-tensor-parallelism
Guidance for implementing tensor parallelism in PyTorch, including ColumnParallelLinear and RowParallelLinear layers. This skill should be used when implementing distributed tensor parallel operations, sharding linear layers across multiple GPUs, or simulating collective operations like all-gather and all-reduce for parallel computation.
Packaged view
This page reorganizes the original catalog entry around fit, installability, and workflow context first. The original raw source lives below.
Install command
npx @skill-hub/cli install benchflow-ai-skillsbench-torch-tensor-parallelism
Repository
Skill path: registry/terminal_bench_2.0/letta_skills_batch/terminal_bench_2_0_torch-tensor-parallelism/environment/skills/torch-tensor-parallelism
Guidance for implementing tensor parallelism in PyTorch, including ColumnParallelLinear and RowParallelLinear layers. This skill should be used when implementing distributed tensor parallel operations, sharding linear layers across multiple GPUs, or simulating collective operations like all-gather and all-reduce for parallel computation.
Open repositoryBest for
Primary workflow: Ship Full Stack.
Technical facets: Full Stack.
Target audience: Development teams looking for install-ready agent workflows..
License: Unknown.
Original source
Catalog source: SkillHub Club.
Repository owner: benchflow-ai.
This is still a mirrored public skill entry. Review the repository before installing into production workflows.
What it helps with
- Install torch-tensor-parallelism into Claude Code, Codex CLI, Gemini CLI, or OpenCode workflows
- Review https://github.com/benchflow-ai/SkillsBench before adding torch-tensor-parallelism to shared team environments
- Use torch-tensor-parallelism for development workflows
Works across
Favorites: 0.
Sub-skills: 0.
Aggregator: No.