A conversion to rectified flow of the Chenkin 0.2

For main model description please refer to this model repo.

RF allows this model to get away from greyness of the base EPS solutions, provides vivid colors and unlocks better lighting adherence, like very dark or contrasty scenes, while not requiring training-time tricks like offset noise.

It also allows to sustain high stability at wide range of CFG, while not suffering from common downfalls of other base models.

Developed by: Cabal Research (Bluvoll, Anzhc)
Compute provided by: Chenkin, Heathcliff
License: fair-ai-public-license-1.0-sd
Finetuned from model: ChenkinNoob-XL-V0.2

Same as your normal inference, but with addition of SD3 sampling node, as this model is Flow-based.

Recommended Parameters: Sampler: Euler, DPM++ SDE, etc. Steps: 20-28 CFG: 3-6 Shift: 3-8 Schedule: Normal/Simple/SGM Uniform/Beta Positive Quality Tags: masterpiece, best quality, aesthetic

Negative Tags: worst quality, normal quality, bad anatomy, low resolution

ChenkinNoob-XL-v0.2 Rectified-Flow - v0.2