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
"I’d like to support this request. It would be beneficial if the developers could add support for the Chroma model.
Chroma is an 8.9B parameter model based on FLUX.1-schnell. More information can be found here: huggingface.co/lodestones/Chroma
Additionally, ai-toolkit and the diffusion-pipe project at github.com/tdrussell/diffusion-pipe already supports Chroma. (LoRA/fine-tuning).
Thank you for the fantastic sd-scripts project; your work is greatly appreciated!"
I came across this comment by blackmagix24. I will give diffusion pipe a shot. if you happen to test it in the future, I would love to see a video from you for chroma fine tuning along with a comparison with flux dev
yeah, when I tried chroma the images weren't as good as flux dev, but on the bright side chroma has apache license and I was wondering if finetuned well, will the results be in par with flux dev.
Thank you lodestones for the high quality model. --model_type option is added to flux_train_network.py. For Chroma, --model_type chroma is required. According to lodestones, --apply_t5_attn_mask --...
Hi! I just downloaded Kohya and all necessary models in my Runpod. How can I use best configs json file(e.g. 48GB_GPU_Quality_Tier_1_40000MB_9.3_Second_IT_Trains_T5_and_T5_Attention) in Kohya?
And I tried this config with L40S, but keep shows "torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 72.00 MiB. GPU 0 has a total capacity of 44.52 GiB of which 24.25 MiB is free. Process 165082 has 44.49 GiB memory in use."
I just checked and it's all 1024 * 1024. Is there any possibility that I'm facing OOM even though I'm using L40S(And I checked the memory usage right before the training)
@Furkan Gözükara SECourses When I change config to "cache_latents = false / cache_latents_to_disk = false", GPU usage dropped to 36GB. Is there any quality drop if I change it like this?
Hi @Furkan Gözükara SECourses Thank you for the dreambooth training tutorial, it really very clear and I successfully manage the training for a person and it performs really well
I have question for other case, if I want to train a person with specific clothing style and also in a specific illustration style, what will be the best approach? Shall I train first the illustration style, then the person with his specific clothing style? The aim is I want to generate this person in consistent clothing style and in consistent illustration style.
Ah I see. Previously I already prepare the character with correct clothing and the desired illustration style. But I have only this one image.
I plan to create other pose and other situation using Flux Kontext. Will it perform better if I do the train in one go, it has full body clothing style and also illustration style?
I am using your Kaggle Kohya ss file to start a kohya ss gradio ui, but it fails by saying no conda environment found, and if i manually start i and try to load a json file forf the configuration, it says something like 'str' has not attribute 'get'? please help