Shypd.aiThe largest open index of AI toolsScore-Entropy-Discrete-Diffusion is an open-source research tool providing a PyTorch implementation for discrete diffusion modeling. It focuses on estimating data distribution ratios, offering a modular framework for generative AI research.
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Score-Entropy-Discrete-Diffusion offers a PyTorch implementation for discrete diffusion modeling, specifically designed for estimating the ratios of the data distribution. Recognized as an ICML 2024 Best Paper, this codebase is built with a modular architecture to foster future research in generative AI. Key components include `noise_lib.py` for noise schedules, `graph_lib.py` for the forward diffusion process, and `sampling.py` for various sampling strategies. Researchers can easily install the environment, load pretrained models from Hugging Face, and run sampling or conditional sampling experiments. The tool also provides comprehensive training code with configurable hyperparameters, making it suitable for developing new discrete diffusion models.
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