PyTorch Lightning Bolts
A collection of models, callbacks, and datasets to extend PyTorch Lightning for applied AI/ML research and production.
What is PyTorch Lightning Bolts?
PyTorch Lightning Bolts is a toolbox of reusable components that extends the PyTorch Lightning framework for deep learning. It provides production-ready models, specialized callbacks, and curated datasets to accelerate AI/ML research and deployment. The library solves the problem of repeatedly implementing common patterns by offering battle-tested components that work seamlessly with PyTorch Lightning workflows.
AI/ML researchers and engineers using PyTorch Lightning who need reusable components for applied research and production deployment. It's particularly valuable for teams wanting to avoid reinventing common patterns while maintaining clean, structured code.
Developers choose Bolts because it provides carefully curated, production-tested components that seamlessly integrate with PyTorch Lightning's structured approach. Unlike building everything from scratch, Bolts offers optimized callbacks, models, and datasets that accelerate development while maintaining best practices for training and inference.
Overview
Toolbox of models, callbacks, and datasets for AI/ML researchers.
Use Cases
Best For
- Accelerating PyTorch Lightning training with optimization callbacks like ONNX conversion
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