Train custom LoRA models for consistent characters, objects, and styles
A limitation of generative models is that they can only generate things they’ve been trained on. But what if you want to consistently compose with a specific object, person’s face, or artistic style not found in the original training data? This is where Eden trained models come in.Models are custom characters, objects, styles, or specific people which have been trained and added by Eden users to the Eden tools’ knowledge base, using the LoRA technique. With models, users are able to consistently reproduce specific content and styles in their creations.Models are first trained by uploading example images to either the Flux or (Older) SDXL Trainer. Training a model takes a couple of hours. Once trained, the model becomes available in all endpoints, including images and video.
Training resolution. Lower (768) useful for faces in larger scenes.
Training at lower resolutions (e.g. 768) can be useful if you want to learn a face but prompt it in settings where the face is only part of the image. Using init_images with rough shape composition helps in this scenario.
Model artistic styles or genres, focusing on abstract characteristics rather than content.With style models, you don’t need to reference the concept - just prompt normally and the style will be applied.Styles can capture various aesthetics, color palettes, layout patterns, or abstract notions like knolling:
Reference in prompts:
Prompt examples:
With style models, you don’t need to reference the concept - just prompt normally and the style will be applied.
Styles can capture various aesthetics, color palettes, layout patterns, or abstract notions like knolling:
