license: creativeml-openrail-m
tags:
- stable-diffusion
- text-to-image
The embeddings in this repository were trained for the 768px Stable Diffusion v2.0 model. The embeddings should work on any model that uses SD v2.0 as a base.
Knollingcase v1
The v1 embeddings were trained for 4000 iterations with a batch size of 2, a text dropout of 10%, & 16 vectors using Automatic1111's WebUI. A total of 69 training images with high quality captions were used.
Knollingcase v2
The v2 embeddings were trained for 5000 iterations with a batch size of 4 and a text dropout of 10%, & 16 vectors using Automatic1111's WebUI. A total of 78 training images with high quality captions were used.
Knollingcase v3
The v3 embeddings were trained for 4000-6250 iterations with a batch size of 4 and a text dropout of 10%, & 16 vectors using Automatic1111's WebUI. A total of 86 training images with high quality captions were used.
Knollingcase v4
The v4 embeddings were trained for 4000-6250 iterations with a batch size of 4 and a text dropout of 10%, using Automatic1111's WebUI. A total of 116 training images with high quality captions were used.
Usage
To use the embeddings, download and then rename the file to whatever trigger word you want to use.
The knollingcase style is considered to be a concept inside a sleek (sometimes scifi) display case with transparent walls, and a minimalistic background.
Suggested prompt words are: "photorealistic", "octane render", & "very detailed". Suggested negative prompts words are: "blurry" and you can add "toy" to make outputs more realistic looking.
Suggested prompts:
<concept>, micro-details, photorealism, photorealistic, <kc-vx-iter>
# Negative prompts
blurry, toy, cartoon, animated, underwater
photorealistic <concept>, very detailed, scifi case, <kc-vx-iter>
<concept>, very detailed, scifi transparent case, <kc-vx-iter>