BustyWomen - LTX https://civitai.red/models/2736657/bustywomen-ltx Based on an entirely new videos-only dataset created using the latest Busty Women Wan model, this LoRA for LTX 2.3 works for both image-to-video and text-to-video. Although the model is primarily created to provide bustier women with bra sizes pushing into the middle of the alphabet, it works equally well in I2V scenes with women of any bust size. The model works very well as a general-purpose motion video for female characters, as illustrated by the variety of shapes and sizes in the samples above. All of the samples include full caption text so you can see how everything is made, and I2V vs. T2V are labeled in each sample as well. I've also tested applying this model to existing LTX character models with very good results, example videos to be posted momentarily. The good: • Really great image-to-video performance, the motion is very realistic. • When the character isn't moving, the model does not add any extra motion. Motion is only added when appropriate. • Works seamlessly with other character LoRAs. • Does not have visible effect on faces when added to a character or starting frame. The bad: • Naked breasts don't look as good as I hoped. The nipples and sometimes other anatomy isn't great. I'd like to fix this in a future version. • Sometimes extra nipple bumps are added to clothing. When this happens, you can often correct it by using a different sampler or reducing the LoRA strength, although this can also change other parts of the video. • My dataset videos were all square videos from the neck down in order to prevent having a face bias, but this means the output will often show the character from the neck down. This can usually be worked around with extra prompting for face details and camera angles that encourage the face to be in frame. I'm not sure how to do this differently in a future version since I don't think LTX training supports an alpha channel to censor out the face from the dataset videos. If anyone has any suggestions, I'd love to hear them. While I generally prefer the output from the LCM sampler, that sampler does seem more likely to give neck-down output. Switch the first pass sampler to something like dpm++_2m_sde ("dpmpp_2m_sde") or res_2s if you have this problem.