BeatriXL Huge Liminal V1 SDXL [fp8/bf16/fp32]

https://civitai.red/models/1493164/beatrixl-huge-liminal-v1-sdxl-fp8bf16fp32?modelVersionId=1690454

A heavy finetune with nearly 500k samples on strictly a smaller liminal dataset to refine BeatriXL into an artistic and tasteful liminal image generating monster.This tool is far beyond simply generating depictions of interesting areas or sectors of an image; you have advanced control of your world in many shapes and forms. Albeit stubborn at times, this beast can be tamed; as it's compatible with most loras if you set the lora to low strength from most SDXL models.You won't just get regurgitated art from a list with this one. It's generating unique cross-entropic contaminated sectors more often than not; and the outcomes reflect high complexity differences - beautiful differences if you want them to be.Euler or Euler A usually works, but I advise using the RES4LYF sampler pack to really make this model's showcase powerful.https://huggingface.co/AbstractPhil/Liminal-Full/tree/main/Beatrix-LORAhttps://huggingface.co/AbstractPhil/Liminal-Full/tree/main/Beatrix-LORA-V2You can pick the mix out yourself if you want. It's a few loras; where one was merged into the core and then the final lora epochs trained from that.liminal, no humans, stuffThe dataset was trained with a multitude of timesteps for a long time with multiple different datasets. Careful though, BeatriXL is still fairly unstable - the refinement helps a whole lot, but if you aren't careful you'll see things you don't want to see. However, this version is a lot more SFW by default than the others - meaning it's more likely to default to a SFW topic than a NSFW topic, but there are no guarantees.If you use humans you're probably going to see something you don't want to see, so be careful with those.Roughly 5k different images; so not many. However, those 5k images were issued a series of different captions from plain English to full description.Joycaption 2 + siglip, GPT4o, LLAMA2 LLAVA B-OMEGA + Siglip500, CLIP_L interrogation, CLIP_G interrogation, and pure raw tags from the WD14 systems.The curriculum training went really well.For the fp8_e4m3fnif your ComfyUI gives you any major errors place these in your gpu launch bat;--fp8_e4m3fn-unet --fp8_e4m3fn-text-enc --fp32-vaeIt's not a true fp8 utilization; as ComfyUI did not autocast to fp8, but instead cast to bf16 manually for me.model weight dtype torch.float8_e4m3fn, manual cast: torch.float16Yet I definitely launched with float8_e4m3fn as the unet. I really don't know what to say about that, other than it's likely not supported by a 4090 so it'll only run on higher-end cards.The text encoders run just fine on fp8.Likely in this code here, as it's running "should_use_bf16", which probably forces it into bf16 mode. Until I have a proper workaround it'll have to be upscaled to bf16, but at least the size is tiny.