Hi HN, we're releasing weights for our latest text to image model and publishing this writeup on how we trained it in quite a bit of depth.
I hope there is something in the report for everyone, we included a fair bit on the actual training and data infrastructure usually not written about much, that I think will be interesting to people here. There's more that didn't fit, happy to answer questions!
This is a massive technical report for an open weights image gen model. As someone who has followed this space closely, it’s really cool to read about the behind-the-scenes experimentation and effort that went into the final product. I hope you will release some of the find tuning tools so the community can experiment with them as well and really push what the model’s capable of.
You can find some links and details in the GitHub readme for finetuning / LoRA support. Ostiris, musubi tuner, fal and hugging face diffusers are all day-0 supported :) https://github.com/krea-ai/krea-2
We recommend training off the undistilled, Raw checkpoint, and then applying the LoRA to the Turbo model for inference.
It's pretty great that you are providing the undistilled model on day 0. Here's a pro-tip: With Flux.2 Klein, someone created a turbo slider LoRA - basically a diff of the turbo 9B model vs. the undistilled 9B model. What's great about this LoRA is that you can sample using a heavier weighting of the undistilled weights during early sampling steps and then finish the sampling off with mostly the distilled weights. The result is a better "finish" (taking advantage of the distilled model's refinement for image quality) without sacrificing the undistilled model's greater ability to adhere to the prompt, because the undistilled model doesn't have to devote its weights so much to looking good.
Thanks! You should definitely check out the r/stablediffusion sub-reddit; people are going crazy over it!
We also had 0-day support from people like Ostris and ComfyUI from the open source community
Neat! Between Ideogram4, Flux2, Qwen-Image, ZiT, and Krea - there's been a lot of positive movement in the open-weights space.
The original Flux.1 Krea is actually in my GenAI Showdown benchmark site from all the way back in July of last year (which feels like a lifetime in this space), so I’m looking forward to putting this new one through its paces.
What is Krea's approach to content such as pornography and gore? It's been frustrating to see all of the leading models take a very hard line on excluding vice content, even when it is perfectly legal, in the name of safety.