Although the weights aren't available, I wanted to note that the model source itself is actually available at https://github.com/openai/guided-diffusion.
Official code for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral)
This new approach to generative modelling looks very intriguing.
In a similar ilk, there's this ICLR paper from this year using stochastic differential equations for generative modelling: https://arxiv.org/abs/2011.13456
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[D] Are DDPMs a variation on Score Based Generative Modeling? Or is there a fundemental difference between the two?
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[D] Efficient, concurrent input pipelines in JAX?
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[D] Variance of sampling in diffusion models
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[D] Why is the diffution model so powerful? but the math behind it is so simple.
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Generate new images from any user-based inputs! Say goodbye to complex GAN and transformer architectures for image synthesis tasks. This new method can do it using only noise!
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