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 really don't understand why it's better to train dreambooth instead of lora, when - larger size - can be trained more slowly - you are bound by the limitations of the basic model - requires much more resources While training the Lora - fewer pictures are enough - faster (about 15 minutes for an SD 1.5 model, SDXL 1 hour) - requires fewer resources, can be trained on local machines - can be used with multiple base models - the same quality can be achieved for persons as for dreambooth. So I used to train dreambooth because I don't need it, I can train what I want on Lora, be it style, object, person or concept. In very special cases I would only train basic model. So why do you train dreambooth instead of lora?
Back when Lora came out, even I was training dreambooth. Then I took the Lora out of it, and the quality of the resulting Lora didn't deliver what the dreambooth could. However, the loras that have been trained recently can do what the extracted lora could not. The new optimizers give very good results with loras. When you train a model with dreambooth, you only train a small part of the whole model, not the rest. And Lora is just that small part. If I were to train a separate dreambooth model for each person, I would need several, many terrabytes of hard disk. Even the Lora's take up a lot of space.
I show how to install Automatic1111 Web UI & ControlNet extension installation from scratch in this video. Moreover I show how to make amazing QR codes and inpainting and out painting of ControlNet which are very similar to Photoshop generative fill and Midjourney zoom out. Furthermore, I explain and show what are Canny, Depth, Normal, OpenPose...