huggingface / huggingface/diffusers

FluxKlein Training Scripts - CFG issue

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Descrizione

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?

Guida per i contributori

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Direzione di ricerca

Start with src/diffusers/pipelines/flux2/pipeline_flux2_klein.py around line 592, then compare the CFG handling in examples/dreambooth/train_dreambooth_lora_flux2_klein_img2img.py and the corresponding FluxKlein training script. Trace how prompt dropout and classifier-free guidance are handled for distilled and non-distilled models; done means the expected behavior and any required training-script or documentation change are established.

Scritto dal modello di indicizzazione a partire dal testo della issue.

Valutazione

Stack tecnologico
python, pytorch
Ambito
machine-learning
Tipo di issue
Bug
Difficoltà
4/5
Tempo stimato
3-5 giorni
Stato di attività
Tranquilla
Chiarezza
Abbastanza chiara
Idoneità per principianti
45/100

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