FluxBooru is a series of models that are trained on a collection of SFW booru images, aesthetic photos, and artistic uh.. anatomy. It doesn't know the kind of positioning information that 🐴 does, if you get my drift. This model was not trained on tags. The tags were used as ground truth for captioning via multiple VLMs.
What FluxBooru tries to offer is a better base model for finetuning and inferencing illustrative artworks. This has been a problem area for tuning the base Dev and Schnell models, which resist illustrative training like it's got a counter-intelligence operation going on inside it.
These models received serious amount of compute. 32x H100s were used with 16 of them dedicated to multi-node training, and two other nodes split between various training jobs.
Approx. 2500 H100 GPU hours have been burned on these weights.
FluxBooru v0.1 is the first release (Dev-based)
Requires classifier-free guidance (CFG) at inference time
This slows down (ComfyUI impl) or slows it down less but requires more VRAM (batched CFG in Diffusers)
Use a value around 5.0 but lower values look less cooked, w/ anatomy issues
The Flux Guidance value can't be set to 1.0 but still has some kind of impact.
Has obvious issues and mostly serves as an artifact for continued training in the same direction, since it is less biased than v0.2 and was trained in full.
Requires ~20-25 steps
An attempt was made at de-distilling Schnell
but even it seems, 32x H100 isn't enough for that job, and it was abandoned.
Not worth testing, doesn't really function at all.
Offered incase anybody looking to do the same would like somewhat of a head start.
FluxBooru v0.2 is a continued training run of v0.1
Requires classifier-free guidance (CFG) at inference time
Same caveats about speed as with v0.1
CFG remains restricted to ~5.0-6.0 with slight improvements in acceptable range
Much better results while still not much character name knowledge learnt in such a relatively short training session (1.6 million seen samples, not even 1 full epoch)
Requires 20-25 steps
https://huggingface.co/terminusresearch/flux-booru-v0.2/tree/main
FluxBooru v0.2-LoKr 1.6B is a LyCORIS LoKr adapter trained to target the full FluxBooru-v0.2 model
Requires classifier-free guidance (CFG) at inference time
But can be merged into Flux.1 Dev, and then use without CFG
Works in ComfyUI, Diffusers
Can be merged into the base FluxBooru-v0.2 model
Has much improved reliability over the base v0.2 model as the LoKr adapter trained much faster and more robustly than the full finetuning had
Works with an expanded CFG range
https://huggingface.co/terminusresearch/FluxBooru-v0.2-LoKr-1.6B
The validation samples here are with too-low of a CFG value and are not representative of the final model's quality
FluxBooru v0.1-LoKr-1.3B is a LyCORIS LoKr adapter trained against the Flux.1 Dev base model
Does not require classifier-free guidance at inference time
The fastest option out of all of the above.
Works in ComfyUI, Diffusers
Can be merged into the base Flux.1-Dev or Schnell models
Weaker impact and not as fun to use. Might have had an issue during training.