With SDXL right around the corner, it seems that the era of 1.5 models is about to come to an end. That doesn't mean that 1.5 models will instantly be left in the dust, in fact, it will probably take a considerable amount of time before we get the same level of customization and finetuning for XL as we currently have with 1.5 models, so 1.5 models will continue to dominate until further work is done to XL, and SenBlend 1.9 represents the pinnacle of the old era of models. This is hopefully the last and best 1.5 model for realism.

SB1.9 is made up of a carefully curated mix of ZovyaV2, Reliberate, Photon, and of course, SenBlend 1.8.

Tips for Dreamboothers:

This model works sublime for Dreambooth, much more so than previous models. I am going to share my magic formula for creating perfect dreambooths every single time. (Keep in mind that current dreambooth versions are usually broken or complete crap. You have to use an older version!):

• A1111 (not Kohya!). Get yourself an older version. Specifically, I use this commit: ea9bd9fc7409109adcd61b897abc2c8881161256

• Use this dreambooth revision: 43ae9d55531004f1dedaea7ac2443e9b16739913

Software versions (you can see this list when you boot up A1111):

• [+] bitsandbytes version 0.35.0 installed.

• [+] diffusers version 0.10.2 installed.

• [+] transformers version 4.25.1 installed.

• [+] xformers version 0.0.16rc425 installed.

• [+] torch version 1.13.1+cu117 installed. This is the most important component, do not upgrade it!

• [+] torchvision version 0.14.1+cu117 installed.

Dreambooth Training Parameters (leave anything not listed at default):

• Extract EMA Weights.

• Training Steps Per Image (Epochs) = 7,360/X where X == Total Number of Subject Images. If you can spare the training time, multiply this by 3 for extra leeway.

• Batch Size: 1-8 depending on your VRAM, it is suspected (though not confirmed) that lower batch size = better quality results. Experiment and report back with your findings.

• Gradient: 1.

• Set Gradients to None: Check.

• No Gradient Checkpointing.

• Gradient Acc Steps: 1

• Class Batch Size: 1

• Learning Rate Scheduler: constant

• Learning Rate = 1.5e-06 to 1.65e-06 works best! Experiment around this range and try not to deviate too much from it.

• Constant/Linear Starting Factor = 0.5

• Scale Position = 0.25

• Use EMA: Yes

• 8bit Adam

• Mixed Precision: bf16 (if you have puny VRAM, go for fp16)

• Memory Attention: flash_attention (using xformers WILL break your model, don't say I didn't warn you!)

Happy Dreamboothing and let me know in the comments if you have questions!