"Denoising Diffusion Implicit Models - best at inpainting":"Denoising Diffusion Implicit models - 最擅长内补绘制",
"Produce an image that can be tiled.":"生成可用于平铺(tiled)的图像",
"Use a two step process to partially create an image at smaller resolution, upscale, and then improve details in it without changing composition":"使用两步处理的时候,以较小的分辨率生成初步图像、接着放大图像,然后在不更改构图的情况下改进其中的细节",
"Determines how little respect the algorithm should have for image's content. At 0, nothing will change, and at 1 you'll get an unrelated image. With values below 1.0, processing will take less steps than the Sampling Steps slider specifies.":"决定算法对图像内容的影响程度。设置 0 时,什么都不会改变,而在 1 时,你将获得不相关的图像。值低于 1.0 时,处理的迭代步数将少于“采样迭代步数”滑块指定的步数",
"Determines how little respect the algorithm should have for image's content. At 0, nothing will change, and at 1 you'll get an unrelated image. With values below 1.0, processing will take less steps than the Sampling Steps slider specifies.":"决定算法对图像内容的影响程度。设置 0 时,什么都不会改变,而在 1 时,你将获得不相关的图像。\n值低于 1.0 时,处理的迭代步数将少于“采样迭代步数”滑块指定的步数",
"How many batches of images to create":"创建多少批次的图像",
"How many image to create in a single batch":"每批创建多少图像",
"Classifier Free Guidance Scale - how strongly the image should conform to prompt - lower values produce more creative results":"Classifier Free Guidance Scale - 图像应在多大程度上服从提示词 - 较低的值会产生更有创意的结果",