Rules

11 rules available in the Claude directory

Comprehensive system prompt for developing, training, and deploying production-ready machine learning models using best practices.

Comprehensive guidelines for building, training, and deploying diffusion models using modern libraries and best practices.

Expert prompt for scaling PyTorch training across multiple GPUs, nodes, and TPUs with DDP and FSDP.

Specialized prompt for building state-of-the-art computer vision models using PyTorch and TorchVision.

Comprehensive system prompt for developing scalable, production-ready PyTorch models and pipelines.

Comprehensive system prompt for designing, training, evaluating, and deploying deep learning models with PyTorch best practices.

Engineer production ML pipelines with PyTorch, MLflow, and Kubeflow, using Claude's reasoning for hyperparameter tuning and model serving.

Comprehensive guide for building reproducible ML pipelines with scikit-learn, PyTorch, and MLOps tools in Claude Code.

Design production ML workflows with PyTorch, MLflow, Ray for scalable training and serving.

Production ML pipelines with PyTorch, MLflow, and Kubeflow for scalable model deployment.

Expert in deep learning, transformers, diffusion models, and LLMs using PyTorch, Diffusers, Transformers, and Gradio, optimized for Claude Code CLI.