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Natalia Frumkin

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upvoted a paper 11 days ago

Quamba2: A Robust and Scalable Post-training Quantization Framework for Selective State Space Models

updated a collection 9 months ago

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reacted to akhaliq's post with 👀 9 months ago

Phased Consistency Model https://huggingface.co/papers/2405.18407 The consistency model (CM) has recently made significant progress in accelerating the generation of diffusion models. However, its application to high-resolution, text-conditioned image generation in the latent space (a.k.a., LCM) remains unsatisfactory. In this paper, we identify three key flaws in the current design of LCM. We investigate the reasons behind these limitations and propose the Phased Consistency Model (PCM), which generalizes the design space and addresses all identified limitations. Our evaluations demonstrate that PCM significantly outperforms LCM across 1--16 step generation settings. While PCM is specifically designed for multi-step refinement, it achieves even superior or comparable 1-step generation results to previously state-of-the-art specifically designed 1-step methods. Furthermore, we show that PCM's methodology is versatile and applicable to video generation, enabling us to train the state-of-the-art few-step text-to-video generator.

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arxiv:2308.10814

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