pytorch-lightning
Organizes PyTorch code with PyTorch Lightning: LightningModules, Trainers for multi-GPU and TPU, data pipelines, callbacks, logging and distributed training.
- Kind
- Skill
- Works with
- Claude Code, Codex, Cursor, Gemini / Antigravity
- Languages
- Python
- Source
- Scientific Agent Skills (K-Dense) @ 5f2bc0341354
- Path
- skills/pytorch-lightning/SKILL.md
- Jobs
- Implementation
- Topics
- Machine learning, Data pipelines
Credit
- Made by
- K-Dense-AI
- Original
- github.com/K-Dense-AI/scientific-agent-skills/blob/5f2bc03413…
- License
- MIT
Listed by Skill Manifest; not made by us.
InstallInstall it by hand, following the source.
gh skill install K-Dense-AI/scientific-agent-skills pytorch-lightning
Install factsScanned 2 Nov 2026
- Adds
- .claude/skills/pytorch-lightning/ (the skill folder)
- 10 file(s) the skill refers to
- Runs scripts
- Yes
- allowed-tools includes Bash
- shell block in the text
- Uses the network
- Yes
- downloads Python packages
- Needs secrets
- Yes
- credentials
- Source revision
- 5f2bc0341354
- Licence
- MIT
- Last activity
- 26 Oct 2026
- Review
- Reviewed
Found by a static scan of the stored text; nothing is run. “None found” is not a guarantee, so read what you install before you run it.
- Only the main file is read; other files in the folder are not scanned
# PyTorch Lightning ## Overview PyTorch Lightning is a deep learning framework that organizes PyTorch code to eliminate boilerplate while maintaining full flexibility. Automate training workflows, multi-device orchestration, and implement best practices for neural network training and scaling across multiple GPUs/TPUs. **Reviewed release:** [Lightning 2.6.6](https://github.com/Lightning-AI/pytorch-lightning/releases/tag/2.6.6), including its checkpoint-loading security fixes. CPU tests use Python 3.11, Torch 2.14.1 and Lightning 2.6.6. Use `import lightning as L` with the `lightning` distribution. The alternative `pytorch-lightning` distribution exposes `import pytorch_lightning as pl`; do not mix class namespaces within one application. GPU, TPU, multi-node and online logger examples are source-verified illustrations, not executed training validation. ## Installation ```bash uv pip install "lightning==2.6.6" ``` Optional extras: ```bash uv pip install "lightning[extra]==2.6.6" # loggers, strategies, etc. uv pip install wandb mlflow # specific loggers as needed ``` ## When to Use This Skill This skill should be used when: …