What is Captum?
Captum is a PyTorch library enhancing AI model interpretability across modalities. It helps researchers and developers gain insights into AI decision-making, enabling transparent and reliable AI systems for image recognition, NLP, and other domains.
How to use Captum?
Integrate Captum into your PyTorch workflow. Apply its interpretability methods using attribution techniques to uncover decision factors. The intuitive interface makes complex model interpretation accessible to both beginners and experienced AI professionals.
Core features of Captum?
Captum offers gradient-based attribution, layer-wise relevance propagation, and integrated gradients. It supports multiple interpretability approaches including occlusion, noise tunnel, and concept activation vectors for various AI architectures.

