Hi everyone,
I am not sure whether it is a bug or not....but since the example training scripts and the pipeline as well try to lump the distilled and non-distilled versions together - it is a bit confusing.
So if one using this model:
https://huggingface.co/black-forest-labs/FLUX.2-klein-base-4B/tree/main/transformer
In the pipeline:
https://github.com/huggingface/diffusers/blob/main/src/diffusers/pipelines/flux2/pipeline_flux2_klein.py#L592
we will have do_classifier_free_guidance evaluated as being true. Which operates only on the prompt level (this is fine, I guess).
however neirther fluxklein nor fluxklein_img2img training scripts:
https://github.com/huggingface/diffusers/blob/main/examples/dreambooth/train_dreambooth_lora_flux2_klein_img2img.py
do not have any dropouts for the prompt during the training. Is there any other mechanism to ensure CFG is actually working that is not clearly documented or there is something else?
Hi everyone,
I am not sure whether it is a bug or not....but since the example training scripts and the pipeline as well try to lump the distilled and non-distilled versions together - it is a bit confusing.
So if one using this model:
https://huggingface.co/black-forest-labs/FLUX.2-klein-base-4B/tree/main/transformer
In the pipeline:
https://github.com/huggingface/diffusers/blob/main/src/diffusers/pipelines/flux2/pipeline_flux2_klein.py#L592
we will have
do_classifier_free_guidanceevaluated as being true. Which operates only on the prompt level (this is fine, I guess).however neirther
fluxkleinnorfluxklein_img2imgtraining scripts:https://github.com/huggingface/diffusers/blob/main/examples/dreambooth/train_dreambooth_lora_flux2_klein_img2img.py
do not have any dropouts for the prompt during the training. Is there any other mechanism to ensure CFG is actually working that is not clearly documented or there is something else?