Hassaku MOSS
The model was trained on a small but dense dataset of 120k images, it still produces realistic-looking results, especially when no characters are involved or the prompt uses natural language. Adding “nose” as a negative tag helps. This is a test to see if MOSS can be trained at all (it can be trained). Look at About this version for more details ->
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Images for training captioned by my own captioner
Supporters
Special thanks to my supporters:
Estryark, SETI, Kodokuna and dataset captioners mariotheknight and tamashiicolle
Recommended Resolutions for MOSS
Here are some resolution suggestions:
1536 × 640
1344 × 768
1216 × 832
1152 × 896
1024 × 1024
896 × 1152
832 × 1216 — most recommended
768 × 1344
640 × 1536
Larger resolutions are possible.
Note: It is a Diffusion Transformer (DiT) model, it is less restrictive on sizes in compare to a Unet like Illustrious, you can use bigger resolutions.
Steps： 30–50 CFG Scale： 3-5
Negative:
worst quality, watermark, jpeg artifact, blurryAdd "nose", if needed
Description
The model was trained on a small but dense dataset of 120k images, it still produces realistic-looking results, especially when no characters are involved or the prompt uses natural language. Adding “nose” as a negative tag helps. This is a test to see whether MOSS can be trained at all. The style isn’t stable and I don’t want to push it further, since backgrounds and especially text degrade quickly. MOSS is large and expensive to train, so I’m waiting for the art/anime variant to be released and will focus on that instead.
Trained on my own custom trainer with a modified muon optimizer, based on Periodic Row-wise Muon but intead of adamW in MuonW, with adafactor. Captions consisting of long NL, short NL, tags with only normal quality tags like "masterpiece".
Note: Those 120k images made MOSS mostly more acceptible for my style merge. It is slitly more stable at NSFW in compare to base MOSS, so far i see, but it was only one epoch on a relative low and save LR.