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Tools for inspecting and logging resolved model parameters to verify experimental training and testing settings.
Distinct from Model Configuration Settings: Focuses on the verification and printing of active parameters for debugging, rather than the act of adjusting settings.
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mmagic is a multimodal training pipeline and framework for generative AI, focusing on visual synthesis and restoration. It provides the infrastructure to build and train models for tasks such as text-to-image and text-to-video generation, 3D-aware content synthesis, and high-fidelity image translation using diffusion models and generative adversarial networks. The project distinguishes itself through specialized capabilities for generative model personalization, including techniques for fine-tuning subjects and styles. It also supports advanced visual manipulations such as latent space interp
Provides capabilities to print and verify the resolved set of parameters used during training and testing.