#57810
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Bigger is not Always Better: Scaling Properties of Latent Diffusion Models
Book •
This research investigates how the size of latent diffusion models affects their sampling efficiency.
It reveals that smaller models can outperform larger ones under certain inference budgets, offering insights into optimizing model size for better performance.
It reveals that smaller models can outperform larger ones under certain inference budgets, offering insights into optimizing model size for better performance.
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Mentioned in 1 episodes
Mentioned in relation to the scaling properties of latent diffusion models.
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