cascade_lab

■I trained Dora on a dataset of 400,000 images.

This one is intended for Cascade 3.6B.

■Training Data (52.58 KB):It also includes a README with my inference workflow, OneTrainer training settings, and tips. Looking through it should give you a deeper understanding of Cascade.

■This Dora is primarily designed to be applied to the Cascade 3.6B base model, but I believe it can also be used with models that have been fine-tuned by others.

■The Dora has been trained at multiple resolutions: 768, 1024, 1280, and 1536px.

Because of this, it allows for very flexible inference. In my workflow, it enables image generation at 3200×4800px.

■Achieving this resolution was possible thanks to the extensions, models, and workflows created by ClownsharkBatwing. He is a dedicated explorer of Cascade, and without his work, I wouldn’t have been able to complete this training. I want to take this opportunity to express my gratitude.

Of course, this Dora can also be used with the standard Cascade workflow without any extensions. However, I personally prefer ClownsharkBatwing’s approach, as I find it more intuitive.

■Beyond that, there are many other contributors to Cascade. Thanks to their efforts, I am still able to continue experimenting with inference and training. I deeply appreciate everyone who has shared their remarkable results in exploring Cascade’s potential—such as sote, R35ON4NCE, ultrapixel, resonance_lite_r1, and others.

■This Dora was trained on Danbooru tags.

For inference, I recommend using tipo for automatic tag generation, as it tends to produce stable and high-quality results.

Although character tags are included in the training, they were not heavily emphasized. So please consider it more like: popular characters may be possible to generate, but it’s not guaranteed.

Pruned Model bf16 (6.2 GB):This is a DoRA backup from an intermediate stage.
In some cases, the intermediate version might produce better results, so feel free to give it a try.

Training Data (52.58 KB):Inference workflow, training settings, and tips