Jul 26, 2022 · Classifier guidance combines the score estimate of a diffusion model with the gradient of an image classifier and thereby requires training an image classifier separate from the diffusion …

Classifier-Free Guidance的核心是通过一个隐式分类器来替代显示分类器，而无需直接计算显式分类器及其梯度。 根据贝叶斯公式， 分类器的梯度可以用条件生成概率和无条件生成概率表示：

Apr 28, 2024 · First, let’s take a look at the table below which shows the main differences between classifier guidance and classifier-free guidance when using them.

Classifier guidance is a recently introduced method to trade off mode coverage and sample fidelity in conditional diffusion models post training, in the same spirit as low temperature sampling or …

search salimans@google.com Abstract Classifier guidance is a recently introduced method to trade off mode coverage and sample fidelity in conditional diffusion models post training, in the same spirit as …

Dec 15, 2024 · One of the key techniques in diffusion models that has significantly improved their performance is classifier-free guidance. In this post, we’ll explore what classifier-free guidance is, …

Jul 22, 2024 · This blog post presents an overview of classifier-free guidance (CFG) and recent advancements in CFG based on noise-dependent sampling schedules. The follow-up blog post will …

Implementation of Classifier Free Guidance in Pytorch, with emphasis on text conditioning, and flexibility to include multiple text embedding models, as done in eDiff-I. It is clear now that text guidance is the …

May 26, 2022 · In a classifier-free guidance we don't explicitly predict conditioning label (let's say some category: dog, cat, etc.). We just embed condition input and concatenate it with our latent space at …

To understand Classifier-Free Guidance (CFG) in LLMs, we must first understand steering and controllability in gen-erative models. In this section, we first discuss the origins of CFG in text-to …