A model for large breasted waifus or semi-realistic characters.V6 Changelog 2023/06/03:<ul><li>Considering this was my first and most popular LoRA, I figured it was time to improve on it. Probably the last version too. Hyperfusion is more or less the successor to this.</li><li>Less harmful to the overall style, but slightly smaller sizes overall, feels like a good balance</li><li>Wider variety of breast shapes in the dataset<ul><li>Some breast shape tags were added, but hard to say how helpful they are</li></ul></li><li>Uses LoRA LoCon, but does not require any additional extensions to run</li><li>Changed "large breasts" to "big breasts" to match my hyperfusion model tags</li><li>The model prefers resolutions around 640, but can do up to 768 to a degree</li><li>Training tags attached under model download section</li></ul>V5 Changelog:<ul><li>v5 now uses LoRA!</li><li>What changed since v4? I trained a breast size classifier to auto label the dataset which resulted in better control over breast size, and made it easier to generate larger sizes.</li><li>Note that the trigger words in v5 are ordered in the following from smallest size to largest: breasts, large breasts, huge breasts, gigantic breasts</li></ul>V4 Info:the keyword for v4 remains hyperbreasts, if you want better control over the size use v5Notes:I used this to train my image tagging classifiers for breast sizes <a target="_blank" rel="ugc" href="https://github.com/huggingface/transformers/tree/main/examples/pytorch/image-classification">https://github.com/huggingface/transformers/tree/main/examples/pytorch/image-classification</a>

hyperbreasts

This is my first attempt at a LoRA trained model. A1111 now has support for LoRA models!Unlike my previous models that used the trigger word hyperbreasts this one allows you to control the size with one of the tags listed above.If the effect is too strong just lower the strength in the LoRA extension for better quality, but at the trade off of breast size. Training Details:<ul><li>1.8k images</li><li>12 epocs</li></ul><ul><li>690 steps</li></ul><ul><li>learning rate 1e-4</li></ul><ul><li>only Unet training</li><li>base model Av3</li><li>clip skip 2</li><li>random flip</li><li>captions files</li><li>bucketing at 768</li><li>dim 64</li></ul>

Files with SHA256: be7cad31cc2163ffe6eb5eec04eadff5fae409ee8c386ee6cd3dd2552589248b