v1.1.2 - masked loss and strong prior preservation
New stuff
- New
is_regularisation_data
option for datasets, works great - H100 or greater now has better torch compile support
- SDXL ControlNet training is back, now with quantised base model (int8)
- Multi-node training works now, with a guide to deploy it easily
- Configure.py now can generate a very rudimentary user prompt library for you if you are in a hurry
- Flux model cards now have more useful information about your Flux training setup
- Masked loss training & a demo script in the toolkit dir for generating a folder of image masks
What's Changed
- quanto: improve support for SDXL training by @bghira in #1027
- Fix attention masking transformer for flux by @AmericanPresidentJimmyCarter in #1032
- merge by @bghira in #1036
- H100/H200/B200 FlashAttention3 for Flux + TorchAO improvements by @bghira in #1033
- utf8 fix for emojis in dataset configs by @bghira in #1037
- fix venv instructions and edge case for aspect crop bucket list by @bghira in #1038
- merge by @bghira in #1039
- multi-node training fixes for state tracker by @bghira in #1040
- merge bugfixes by @bghira in #1041
- configure.py can configure caption strategy by @bghira in #1042
- regression by @bghira in #1043
- fix multinode state resumption by @bghira in #1044
- merge by @bghira in #1045
- validations can crash when sending updates to wandb by @bghira in #1046
- aws: do not give up on fatal errors during exists() by @bghira in #1047
- merge by @bghira in #1048
- add prompt expander based on 1B Llama model by @bghira in #1049
- implement regularisation dataset parent-student loss for LyCORIS training by @bghira in #1050
- metadata: add more flux model card details by @bghira in #1051
- merge by @bghira in #1052
- fix controlnet training for sdxl and introduce masked loss preconditioning by @bghira in #1053
- merge by @bghira in #1054
Full Changelog: v1.1.1...v1.1.2