Hello everyone. I am Dr. Furkan Gözükara. PhD Computer Engineer. SECourses is a dedicated YouTube channel for the following topics : Tech, AI, News, Science, Robotics, Singularity, ComfyUI, SwarmUI, ML, Artificial Intelligence, Humanoid Robots, Wan 2.2, FLUX, Krea, Qwen Image, VLMs, Stable Diffusion
Man thank you so much I got confused by the many negative feedbacks regarding krea training. From your tests it seems to be a huge improvement over flux.dev. Do you think it would do well with larger datasets as well (200 images ?)
it's a playful joke or nod on how I wanted to train a lora, and it seems a dataset just appeared I like your lora's, and I like your posts.. I appreciate you
I've been testing several samplers and schedulers for the FLUX KREA model, and it's hard to choose just ONE that is the best. It really depends on your creative goal.
However, I think these combinations are definitely worth using:
Sampler: DPM++ 2M Scheduler: bong_tangent (New)
Sampler: Euler Scheduler: Beta / beta57
Sampler: dpmpp_2m or ipndm Scheduler: Beta / beta57
I'm currently running a small test comparing a few options. When it's ready, I'll share the results. However, I'm also waiting for @Furkan Gözükara SECourses comparison, as it will surely be more comprehensive.
That said, it seems impossible to choose one single best combination, as it depends on many factors like the result you want to achieve, the style of the photo, and of course, personal taste. But tests like this are useful because we can rule out the samplers/schedulers that cause issues, like artifacts.