alt Hacker NewsReleasing weights for FLUX.1 Krea
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Nice release. Ran some preliminary tests using the 12b Txt2Img Krea model. Its biggest wins seems to be raw speed (and possibly realism) but perhaps unsurprisingly did not score any higher on the leaderboard for prompt adherence than the normal Flux.1D model.
https://genai-showdown.specr.net
On another note, there seem to be some indication that Wan 2.2+ future models might end up becoming significant players in the T2I space though you'll probably need a metric ton of LoRAs to cover some of the lack of image diversity.
Hi! I'm lead researcher on Krea-1. FLUX.1 Krea is a 12B rectified flow model distilled from Krea-1, designed to be compatible with FLUX architecture. Happy to answer any technical questions :)
Can someone ELI5 why the safetensor file is 23.8 GB, given the 12B parameter model? Does the model use closer to 24 GB of VRAM or 12 GB of VRAM. I've always associated a 1 billion parameter = 1 GB of VRAM. Is this estimate inaccurate?
Tried a simple prompt, and got some pretty interesting results:
"Octopus DJ spinning the turntables at a rave."
The human like hands the DJ sprouts are interesting, and no amount of prompting seems to stop them.
Opinionated, as the paper says.
hey hn! I'm one of the founders at Krea.
we prepared a blogpost about how we trained FLUX Krea if you're interested in learning more: https://www.krea.ai/blog/flux-krea-open-source-release
I've never gotten one to make what I am thinking of: A Galton board. At the top, several inches apart are two holes from which balls drop. One drops blue balls, the other red balls. They form a merged distribution below in columns, demonstrating dual overlapping normal distributions
Imagine one of these: https://imgur.com/a/DiAOTzJ but with two spouts at the top dropping different colored balls
Its attempts: https://imgur.com/undefined https://imgur.com/a/uecXDzI
I recently ran a training experiment using the same dataset, number of steps, and epochs on both Flux Dev and Flux Krea models. What stood out to me was that Flux Dev followed the text prompts more accurately, whereas Krea’s generations were more loosely aligned or "off" in terms of prompt fidelity with deformations in body type and the architecture.
Does this suggest that Flux Krea requires more training to achieve strong text-to-image alignment compared to Flux Dev? Or is it possible that Krea is optimized differently (e.g. for style, detail, or artistic variation rather than strict prompt adherence)?
Curious if anyone else has experienced this or has any insight into the differences between these two. Would love to hear your thoughts
Do you have an NVIDIA optimized version? Similar to how RTX accelerated FLUX.1 Kontext: https://blogs.nvidia.com/blog/rtx-ai-garage-flux-kontext-nim...
Relevant links:
- GitHub repository: https://github.com/krea-ai/flux-krea
- Model Technical Report: https://www.krea.ai/blog/flux-krea-open-source-release
- Huggingface model card: https://huggingface.co/black-forest-labs/FLUX.1-Krea-dev
I'd recommend you offer a clearly documented pathway for companies to license commercial output usage rights if they get the results they seek (i'll know soon enough!)
Non-commercial license... What's the point even, I can't use it for anything.
For the Krea team that might be reading: I was trying to evaluate Krea for my image gen use case, and couldn't find:
- cost per image - latency per image
Hope you guys can add it somewhere!
I usually use https://github.com/axolotl-ai-cloud/axolotl on Lambda/Together for working with these types of models. Curious what others are using? What is the quickest way to get started? They mention Pre-training and Post-training but sadly didnt provide any reference starter scripts.
Amazing. I can practically smell that owl it looks so darned owl-like.
From the article it doesn’t seem as though photorealism per se was a goal in training; was that just emergent from human preferences, or did it take some specific dataset construction mojo?
Thanks for the release to the team! Any plans on doing the same for FLUX.1 Kontext?
Cool to see an open weight model for this. But what's the business use case? Is it for people who want to put fake faces on their website that don't look AI generated?
Helpful blog post for understanding what kind of data is needed for these models!
Does this have any application for generating realistic scenes for robotics training?
uv not working no clicking no torch
and
Cannot access gated repo for url https://huggingface.co/black-forest-labs/FLUX.1-Krea-dev/res.... Access to model black-forest-labs/FLUX.1-Krea-dev is restricted. You must have access to it and be authenticated to access it. Please log in.
I saw this comparison on reddit[1] between Wan2.2 and FLUX.1 Krea and it doesn't look like Krea is successful at avoiding the “AI look”, whereas Wan succeed brilliantly.
[1]: https://www.reddit.com/r/StableDiffusion/comments/1mec2dw/te...
Does it work out of the box with other Flux-compatible tools such as sd-scripts?
yoo i'm also a researcher on the krea 1 project and happy to answer any questions :)
Nitpick: this is not open weights, this is weights available. The license restricts many things like commercial, NSFW, etc.
For Dang or HN-mods:
I noticed that the URL for this submission is wrong: I tried to submit the correct URL (https://www.krea.ai/blog/flux-krea-open-source-release) but, for some reason, the submission gets flagged as duplicated and then I can only find this item which has a URL to our old blog post.
In the mean time, I'll setup a server-side redirect from the old blog post to our new one, but it would be nice to fix the link and I don't think I can do it on my side.
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How did you train while ensuring only images consensually acquired were used?
Hello everyone.
I’m the Co-founder and CTO of Krea. We’re excited because we wanted to release the weights for our model and share it with the HN community for a long time.
My team and I will try to be online and try to answer any questions you may have throughout the day.