Refer to MBHU-TT and MBHU-TT2F for less common tags if you need to but you likely won't need to
License Scope:
Creative License Scope
Online Image Generation
Merge
Allow Downloads
Commercial License Scope
Sale or Commercial Use of Generated Images
Resale of Models or Their Sale After Merging
Model Parameters:
Base Model:
Pony
Epochs:
0
Iteration Steps:
0
Clip Skip:
0
Review:
0
Review
Nobody asked for it, and the 36 hours of training was painful.
The results however, seem to be worth it. Trained with Pony V6 and primarily tested with Everclear. The goal was not to recreate the wheel. Pony handles "most" things contained in this version with satisfactory results, but sometimes there's just a little lacking, like the problem we had with 1.5 and 'flat chested' rendering something closer to 'small breasts'. I used (most of) the training data used in MBHU-TT2FRS but removed tattoos and pregnancy data along with a couple other things I'm less worried about. If you want to refer to TT2FRS for tags, the data that was included uses the same exact files, except with Pony, the results are much cleaner and things like 'small areola' and 'inverted nipples' work much easier.
Nobody asked for it, and the 36 hours of training was painful.
The results however, seem to be worth it. Trained with Pony V6 and primarily tested with Everclear. The goal was not to recreate the wheel. Pony handles "most" things contained in this version with satisfactory results, but sometimes there's just a little lacking, like the problem we had with 1.5 and 'flat chested' rendering something closer to 'small breasts'. I used (most of) the training data used in MBHU-TT2FRS but removed tattoos and pregnancy data along with a couple other things I'm less worried about. If you want to refer to TT2FRS for tags, the data that was included uses the same exact files, except with Pony, the results are much cleaner and things like 'small areola' and 'inverted nipples' work much easier.