PyTorch Lightning

Shows how to organize PyTorch training with Lightning's LightningModule and Trainer, covering validation, DDP, callbacks and learning-rate scheduling.

Orchestra-Research/AI-Research-SKILLs

Organizes PyTorch training code into LightningModules, DataModules and Trainers, with multi-GPU strategies, callbacks and logging configured.

davila7/claude-code-templates

Tracks ML experiments, versions models in the MLflow registry and covers deployment and reproducibility, with autologging for common frameworks.

Orchestra-Research/AI-Research-SKILLs

Explains RWKV, a hybrid that trains in parallel like a GPT and runs inference like an RNN with constant memory per token, plus usage, fine-tuning and troubleshooting.

Orchestra-Research/AI-Research-SKILLs

Shows how to log ML runs, configs, metrics and media with SwanLab and view them in cloud, local or self-hosted dashboards.

Orchestra-Research/AI-Research-SKILLs

Deep learning framework (PyTorch Lightning / lightning package).

K-Dense-AI/scientific-agent-skills

Convert existing PyTorch Lightning training code into an NVFLARE federated job using the Lightning Client API patch, local validation, and job export; use only when the request names…

NVIDIA/skills

PyTorch Lightning framework for scalable model training and research

wentorai/research-plugins