Shypd.aiThe largest open index of AI toolsDenoisingDiffusionProbabilityModel-ddpm- is an open-source tool that implements DDPM for training UNet models. It allows users to train on the CIFAR-10 dataset and observe the denoising process.
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DenoisingDiffusionProbabilityModel-ddpm- is an open-source implementation of the Denoising Diffusion Probability Model (DDPM). This tool provides a straightforward way for developers and researchers to train a UNet model on the CIFAR-10 dataset. Users can directly run `Main.py` to initiate training and then adjust model configurations to visualize the denoising process. The repository also includes `MainCondition.py` for training with Classifier-free guidance. Pre-trained weights for CIFAR-10 are available, and the project references key papers and blogs for deeper understanding of DDPM frameworks, making it an accessible resource for learning and experimentation in diffusion models.
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