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View Code? Open in Web Editor NEWUnofficial Implementation of Consistency Models in pytorch
Home Page: https://arxiv.org/abs/2303.01469
Unofficial Implementation of Consistency Models in pytorch
Home Page: https://arxiv.org/abs/2303.01469
Hello. Why do N(k), m(k) depend on the number of epoch, not on the number of step?
Hello! Your work is truly remarkable. I've had the opportunity to experiment with standard DDPM models using DDIM sampling, and despite being relatively slow, they exhibit a fascinating reversibility property. This allows for seamless transitions between Gaussian noise and images, as well as the reverse process, recreating the exact same input noise.
I would be grateful if you could provide some insights into whether this reversibility property is preserved in Consistency models. The examples provided do not explicitly demonstrate this aspect, and I am eager to learn more about it. Thank you for your time and expertise.
Thanks for the brilliant work! I am reading this legendary paper and get this question that I want to discuss here.
The paper starts at introducing a new method to distill knowledge from a trained score-based model. By Eq. (7) one could easily learn that the function
By then the paper starts to introduce "training consistency models in isolation", and the training objective remains almost the same except that the two points become
I know this is not directly related to this implementation but I'm looking forward to any hint!
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