WIP - DO NOT USE

Still in the middle of getting this description and such fleshed out, so WIP.

🐍 bigASP 3

The next evolution of bigASP has begun. A general purpose diffusion model built on the Flux.2 Klein architecture. Photoreal, anime, cartoons, furry, product photos, you name it. As usual, strong performance both on everyday safe prompts and 🌶️ prompts. A model meant for you to express your creativity.

Start with the RL2 version, and follow Usage below for the best experience.

Usage

• Use the RL2 model

• 20 steps

• Euler or DPM2

• 1.0 Guidance (i.e. disabled)

• Detailed Prompts

• Any Preset Resolution

Drop this image into ComfyUI for a ready-to-go workflow:

Status

bigASP 3 is currently still UNDER DEVELOPMENT. This is a very early ALPHA release. Just to give a taste of the model. The current version has tons of problems and will likely not be useful for your everyday gens.

Pre-training is complete, establishing the base model. Post-training is on-going. The post trained model is stable and usable, but has some odd artifacts (color tint and noise, mostly) and needs a lot more polish and improved photorealism.

Versions

• RL2 - Use this to try bigASP 3 out. Stable and usable.

• Base - This is the pretrained model with no SFT or RL applied. More creative, far less stable.

Known Issues

• Noise/grain - The model loves adding a bit of noise/grain to the images. This is likely the model hacking the "detail" reward during its training.

• Green tint - The model is obsessed with the color green, preferring it over other colors and adding it as a tint to many gens. No idea why, but I'll tweak the Color reward for future runs.

Usage (More details)

The RL2 model was trained on 20 steps, DPM2, with no CFG, and these resolutions:

• Square: 1024 × 1024

• Portrait: 736 × 1472, 768 × 1376, 832 × 1248, 864 × 1152

• Landscape: 1472 × 736, 1376 × 768, 1248 × 832, 1152 × 864

So, generally speaking it will work best within those settings when you use it. It should be able to handle things outside of it. Maybe even 2K resolutions. But it will be generalizing in those settings so performance might be worse.

Both Base and RL2 were trained exclusively on detailed prompts, so the model works best when it has most of the desired image specified. I've trialed it with different kinds of prompting, under prompting, etc, and it doesn't seem to have too much trouble when the prompts are in different wording and formatting, but with underspecified prompts it can be less reliable and image quality will suffer.

Yeah, I know, it's a pain in the butt. But first and foremost I wanted bigASP 3 to follow prompts reliably and well. Prompts can be fixed, the image model less so :P I plan to train a prompt enhancer tuned specifically for bigASP 3. So the recommended flow will be: ask for what you want -> prompt enhancer creatively fleshes that out -> bigASP 3 generates it to the T.

For now I recommend using your LLM of choice to help with prompting.