Type | |
Stats | 121 11 47 |
Reviews | (13) |
Published | Sep 7, 2024 |
Base Model | |
Training | Steps: 2,912 Epochs: 7 |
Trigger Words | censored |
Hash | AutoV2 099F7260A9 |
At the start I'm training only pixelated censoring. I would like to first fine tune dataset/training on understanding of the concept of censoring on any object/part of object with natural language.
Version comparison
ALPHA2 is much more flexible than ALPHA1
ALPHA2 is able to censore things that were not present in training dataset
ALPHA2 has a bit of issues with hands and quality (jpeg artifacts)
ALPHA2 is not censoring things that you do not specify as ALPHA1 did
ALPHA2 does not censore somtimes entire objects (mostly on bigger ones)
How to use
Trigger word censored
It works pretty well with natural language prompts (prompts that seemed to work for me are adding to the end "<something> is/are censored.", before the thing you wanna censore add "censored <something>", or add right behind "<somthing> that is /are censored")
Don't use this LoRA on clip or keep it on strength 1
Known issues
Jpeg artifacts in certain parts of the image
Hands are generated blurry or with wrong number of fingers
If you have some ideas for future types of censoring leave them in the comments.
Enjoy :)