pytorch-fsdp2 SKILL.md skillA
pytorch-fsdp2 from orchestra-research/ai-research-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add orchestra-research/ai-research-skills/pytorch-fsdp2@v1.0.0Pins v1.0.0 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- orchestra-research/ai-research-skills
- Path
08-distributed-training/pytorch-fsdp2/SKILL.md- Versions recorded
- 1
- Latest version
- v1.0.0, committed Jan 30, 2026
- Size
- 10,992 bytes
- Repository stars
- 13,718
- License
- MIT
Adds PyTorch FSDP2 (fully_shard) to training scripts with correct init, sharding, mixed precision/offload config, and distributed checkpointing. Use when models exceed single-GPU memory or when you need DTensor-based sharding with DeviceMesh.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# Skill: Use PyTorch FSDP2 (`fully_shard`) correctly in a training script This skill teaches a coding agent how to **add PyTorch FSDP2** to a training loop with correct initialization, sharding, mixed precision/offload configuration, and checkpointing. > FSDP2 in PyTorch is exposed primarily via `torch.distributed.fsdp.fully_shard` and the `FSDPModule` methods it adds in-place to modules. See: `references/pytorch_fully_shard_api.md`, `references/pytorch_fsdp2_tutorial.md`. --- ## When to use this skill Use FSDP2 when: - Your model **doesn’t fit** on one GPU (parameters + gradients + optimizer state). - You want an eager-mode sharding approach that is **DTensor-based per-parameter sharding** (more inspectable, simpler sharded state dicts) than FSDP1. - You may later compose DP with **Tensor Parallel** using **DeviceMesh**. Avoid (or be careful) if: - You need strict backwards-compatible checkpoints across PyTorch versions (DCP warns against this). - You’re forced onto older PyTorch versions without the FSDP2 stack. ## Alternatives (when FSDP2 is not the best fit) …
Read the whole file at its exact version.
How to install
mdr add orchestra-research/ai-research-skills/pytorch-fsdp2@sha256:b540043bd17d7418The line at the top of this page pins the label v1.0.0, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_jcmew7sldohiy5an)
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Versions
The registry has recorded 1 version of this file, committed on Jan 30, 2026.
Audit of the latest version
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Source
orchestra-research/ai-research-skills · 13,718 stars · license MIT · pushed 2026-10-11 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_jcmew7sldohiy5an GET https://markdownregistry.com/api/v1/resolve?ref=orchestra-research/ai-research-skills/pytorch-fsdp2 GET https://markdownregistry.com/api/v1/blob/b540043bd17d741840843df2f76d556d41be29c82a2acd85565ce2b1ce088a50
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.