Torch-Pruning implements the DepGraph algorithm to enable general-purpose structural pruning across diverse deep learning architectures. Unlike simple masking approaches, it physically removes parameters and their dependencies, reducing model size and computational cost. The toolkit supports off-the-shelf models from Huggingface, Timm, and Torchvision, targeting both large language models and vision models for efficient deployment.