guidance_scale的取值范围 在生成式人工智能模型的参数调节中,guidance_scale是一个直接影响生成结果与提示词关联性的关键参数。这个参数的作用就像炒菜时撒盐的过程——盐放少了菜没味道,放多了又会掩盖食材本身的鲜味。理解它的取值范围对普通人使用AI工具生成图片、文本等内容具有实际指导意义。 绝大多数模型的...
在 Stable Diffusion 的采样中,同样的 guidance_scale 对于不同的 Prompt 影响差异可以非常大。这个问题在使用 negative prompt 的情况下会更明显,所以某些 Stable Diffusion 的界面中会允许用户使用超过 20 的 guidance_scale。原因也很简单,guidance_scale 是个无量纲数,没有任何所谓的物理意义。由于大多数人都热衷...
Characteristic Guidance Web UI is an extension of for the Stable Diffusion web UI (AUTOMATIC1111). It offers a theory-backed guidance sampling method with improved sample and control quality at high CFG scale (10-30). This is the official implementation ofCharacteristic Guidance: Non-linear Correc...
1、摘要 经过DDPM 和 DDIP 和 classifier-guided diffusion model 等技术的发展,diffusion model 生成的效果已经可以超越 GANs,称为一种生成模型的直流。尤其是 classifier-guided diffusion model 可以让生成图像的效果在多样性(FID)和真实度(IS)中权衡取舍。但 classifier-guided diffusion model 需要额外训练一个分类...
2021年OpenAI在「Diffusion Models Beat GANs on Image Synthesis」中提出Classifier Guidance,使得扩散模型能够按类生成。后来「More Control for Free! Image Synthesis with Semantic Diffusion Guidance」把Classifier Guidance推广到了Semantic Diffusion,使得扩散模型可以按图像、按文本和多模态条件来生成,例如,风格化可以...
Not all enterprises adopt Azure in the same way, so the Enterprise-Scale architecture may vary between customers. Ultimately, the technical considerations and design recommendations of the Enterprise-Scale architecture may lead to different trade-offs based on the customer's scenario. Some variation is...
p + aes(colour = cty) + scale_colour_viridis_c(guide = "colourbar_cap") 设置图例为小提琴 代码语言:javascript 代码运行次数:0 运行 AI代码解释 p + aes(colour = cty) + scale_colour_viridis_c(guide = guide_colour_violin(density = mpg$cty)) 设置图例为直方图 代码语言:javascript 代码运...
The measuring instrument in evaluating the psychometric properties is the new version the Woodcock-Johnson Cognitive Ability Scale that has a desirable reliability and validity. Findings: the psychometric findings showed that the instrument in students had validity (internal consistency and homogeneity), ...
<guidisPermaLink="false">https://blogs.msdn.microsoft.com/azurecat/?p=5385</guid> <description> <![CDATA[ The AzureCAT blog is moving to a new home on Microsoft Tech Community!... ]]> </description> <content:encoded> <![CDATA[ The AzureCAT blog is moving to a new home on Microso...
上面两个伪代码中均涉及了一个梯度缩放(gradient scale)参数s。因为作者发现,如果不设置这个值,那么...