Shypd.aiThe largest open index of AI toolsDiffusion-Models-pytorch is an open-source PyTorch implementation of diffusion models. It provides an easy-to-understand version of the DDPM algorithm within 100 lines of code, supporting both conditional and unconditional training.
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Diffusion-Models-pytorch offers an accessible PyTorch implementation of diffusion models, designed for clarity and ease of understanding. Unlike other implementations, this project strictly adheres to Algorithm 1 from the DDPM paper, avoiding lower-bound formulations for sampling, which results in a concise codebase of under 100 lines. It supports both conditional and unconditional training, with the conditional implementation also featuring Classifier-Free-Guidance (CFG) and Exponential-Moving-Average (EMA). The repository includes explanation videos for both the theoretical background and practical implementation, making it an excellent resource for learning and experimenting with diffusion models.
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