mbreuss/consistency_models_toy_task
Unofficial minimal implementation of consistency models (CM) proposed by Song et al. 2023 on a 1D toy task in pytorch
This project offers a minimal exploration of consistency models using simple 1D datasets, like single or multiple Gaussian distributions. It allows researchers and machine learning engineers to experiment with Consistency Distillation and Consistency Training techniques. You provide the 1D data configurations, and the project outputs visualizations of the model's performance in generating new data points based on those distributions.
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Use this if you are a researcher or machine learning engineer looking to understand and test the fundamental behavior of consistency models on simplified, one-dimensional data distributions.
Not ideal if you need to apply consistency models to complex, real-world datasets like high-dimensional images or tabular data, or if you require a production-ready implementation.
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21
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Language
Python
License
MIT
Category
Last pushed
May 02, 2023
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