2 dépôts
Awesome GitHub RepositoriesDiffusion Weight Optimizers
Tools for optimizing weights of diffusion models to enable training on consumer-grade hardware.
Distinct from Diffusion Model Managers: Focuses on the mathematical optimization of weights for training efficiency rather than the organizational management of model files.
Explore 2 awesome GitHub repositories matching artificial intelligence & ml · Diffusion Weight Optimizers. Refine with filters or upvote what's useful.
Awesome Diffusion Weight Optimizers GitHub Repositories
Trouvez les meilleurs dépôts grâce à l'IA.Nous recherchons les dépôts les plus pertinents grâce à l'IA.
- ostris/ai-toolkit
ostris/ai-toolkit
9,509Voir sur GitHubai-toolkit is a diffusion model training toolkit designed for fine-tuning image and video generation models. It functions as a containerized model trainer and GPU training job manager, providing the infrastructure to orchestrate dependencies and manage training processes on remote GPU hardware. The system utilizes low-rank adaptation techniques, including LoRA and LoKr weight optimization, to reduce the hardware requirements for model training. It distinguishes itself through a web-based training controller that allows for the monitoring and modification of hyperparameters, secured by token-b
Optimizes weights for image, video, and audio diffusion models to reduce hardware requirements for training.
Python - xavierxiao/dreambooth-stable-diffusion
XavierXiao/Dreambooth-Stable-Diffusion
7,738Voir sur GitHubThis project is a Dreambooth implementation designed to personalize Stable Diffusion models. It serves as an AI image personalization tool and model tuner that enables the creation of unique subject identifiers to generate consistent, personalized images. The system focuses on subject-driven image synthesis by fine-tuning pre-trained diffusion models on small, custom datasets. This allows the model to recognize specific people, objects, or artistic styles and place those learned subjects into diverse contexts via text-to-image conditioning. The implementation includes a diffusion model optim
Includes a diffusion weight optimizer to manage the mathematical optimization of weights for efficient training on consumer hardware.
Jupyter Notebookpytorchpytorch-lightningstable-diffusion
