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    This model aims to help generate a variant of bursting breasts: breasts that are about to completely burst of clothes and have been pressed into an unusual shape because of that. Basically, the before image of exploding clothes.

    I intend to improve and update this with more views, clothing, etc. as I learn more about training models.

    V2.2
    Another small expansion of the dataset and some retraining. The model is a little more responsive to tag weights and can sometimes do a clothed concept of itself (i.e. breasts bursting out of a bra while wearing a collared shirt over).
    My image saving node messed up, so the example images may not be available for a while. The metadata didn't save to the images themselves and I may or may not get around to manually inputting the generation info for each.

    V2.1

    Slightly expanded the dataset and made an Illustrious model.

    V2.0

    Retagged the dataset with a newer tagging model and slightly modified how the tags work to help with the way breasts spill out. Most important is replacing atb with bursting rbeasts since that produced better results in all my trials. In short, cleavage is breasts spilling from the top, sideboob is from the side, and underboob is from below. In many cases, it's just as important to specify the locations where you don't want spillage as it is to the locations where you do. Tags also seem more stable, so increasing the weight of them even up to 2+ has produced good results.

    XL V1.4

    Finally got around to making this for SDXL. I'd recommend running the SDXL LoRA at 1 normally. SDXL does a way better job of following prompts, so a higher weight seems to add in a style more than it improves the image. Some tags also introduce a style. I'll be trimming the dataset and re-tagging it shortly to try and eliminated this.

    V1.4

    Expanded the dataset by 80 or so images. I also re-tagged every image and combed through the tags to make certain everything looked right. Poses, sizes, and prompts are more consistent as a result. Now combinations like cleavage in the prompt and underboob in the negative should help produce results with only cleavage spilling out of clothes. Likewise, including both cleavage and underboob eliminates most sideboob instances. I also nudge the upper limit of the enormous breasts tag and the wide hips and thick thighs tags are slightly larger on average.


    I'd recommend running this LoRA at 1.3 normally and around 1.3-1.5 when other LoRAs are involved. This LoRA is heavily impacted by the canvas size and orientation. Wider images allow for larger sizes but less diversity, and a more narrow canvas produces more dynamic poses but may force larger tags to generate smaller breast sizes. Don't be afraid to try all sorts of canvas layouts.

    The posted images were upscaled with StableDifusion's built in Anime upscaler to x2 and ran through GFPGAN at a visibility of 0.6.

    V1.3

    Greatly expanded the dataset to help with tag recognition. I also changed some tags around to make the enormous breasts and gigantic breasts tags more more consistent.

    V1.2

    The from side tag now consistently generates images and the from behind tag will generate most of the time. I recommend running this at 1.3 weight. The biggest change is the addition of the enormous breasts tag. This was included to allow for larger sizes than gigantic without making the gigantic breasts tag inconsistent. This new tag favors wider images, so if it seems to generate a smaller size than anticipated, try a 640x512 or 768x512 ratio. If you can't quite get a pose right with view tags, try some helper tags. For instance, I had to use looking away and backboob to get a good from behind pose.

    V1.1

    I made the from-side tag more consistent and finally got the from-behind tag to generate something coherent. From-behind is mostly a proof-of-concept right now. Also made the breast size distinction more impactful.

    V1.0

    Further refined the dataset and added a few more images. Also refined the tagging so side view images could be recognized. The image generation for all sizes from the front seems to be consistent now, but images from the side are hit or miss. The from-behind view is still unsupported.

    V0.2

    Refined the dataset so generation is more consistent and breast sized are more defined.

    To do:

    Fix trigger word
    Fix poor hand generation
    Fix poor nipple generation
    Fix multiple breast generation
    Add side view support
    Add rear view support
    Add top/bottom view support
    Be able to specify if breasts burst from top or bottom
    Try and support smaller breast sizes
    Remove SDXL LoRA adding a style
    Support torn clothes better

    Description

    FAQ

    Comments (11)

    pokezilla39966Jun 2, 2024· 3 reactions
    CivitAI

    BRO, soon as i clicked on this, EYES!! XD, congrats on good eyes, i'll definetely try this out :D

    reggiemccorthy1457
    Author
    Jun 2, 2024· 1 reaction

    No kidding. The machine I was on before only had 4GB of VRAM and I had to jump through all sorts of hoops to get it to generate anything decent. Eyes and fingers absolutely refused to be generated with that machine and checkpoint combination.

    pokezilla39966Jun 2, 2024

    @reggiemccorthy1457 wait, so you upgraded your setup or still have 4gb of vram?

    reggiemccorthy1457
    Author
    Jun 2, 2024· 1 reaction

    @pokezilla39966 I was away at college. I only had access to my laptop there, but now that I'm home for the summer I have access to my desktop again which has bridged GTX 1070s.

    pokezilla39966Jun 2, 2024

    @reggiemccorthy1457 bridged? what do you mean?

    reggiemccorthy1457
    Author
    Jun 3, 2024· 1 reaction

    @pokezilla39966 It's where some GPUs could be connected. GPU companies tried it out I think about a decade or so ago so you could use two lower end GPUs and combine their processing power. It got phased out pretty quick sense it was more difficult to code for and single GPUs started to get better and I don't know of any software nowadays that can make use of it.

    pokezilla39966Jun 4, 2024

    @reggiemccorthy1457 so you have two gtx 1070's? connected? if that's what I'm getting out of what you are saying, that's neato, but when you get the funding, do try to get a single gpu that's 8gb vram or higher.

    reggiemccorthy1457
    Author
    Jun 6, 2024· 1 reaction

    @pokezilla39966 That's the plan. The 1070s are 8gb, but I'm pretty certain they we developed before AI got as popular as it is now. I wouldn't be surprised if a new 8gb card would blow the 1070s out of the water just because the new architectures are designed with AI in mind.

    pokezilla39966Jun 6, 2024

    @reggiemccorthy1457 "NVIDIA's latest Tensor cores, found in its 30 and 40 Series GPUs, offer optimizations tailor-made for AI applications. With all that in mind, your best starting point for AI image generation is an NVIDIA 40-Series graphics card. The ProArt GeForce RTX 4060 is a solid all-around pick at an attainable price." so there is a specific 8gb vram card for ai apps, here, https://www.amazon.com.au/ASUS-ProArt-GeForce-Graphics-DisplayPort/dp/B0CDTVBXMN

    reggiemccorthy1457
    Author
    Jun 9, 2024· 1 reaction

    @pokezilla39966 I'll have to look into some of those. Thanks for the tip.

    pokezilla39966Jun 10, 2024

    @reggiemccorthy1457 no problem.

    LORA
    SDXL 1.0

    Details

    Downloads
    2,464
    Platform
    CivitAI
    Platform Status
    Available
    Created
    6/2/2024
    Updated
    6/12/2026
    Deleted
    -
    Trigger Words:
    atb

    Files