LoRA Generation
Achieve perfect consistency in your AI visuals. LoRA (Low-Rank Adaptation) allows you to inject specific characters, products, or artistic styles into foundation models like FLUX.1 and SDXL. Train your own adapters or choose from our massive library to generate branded content that adheres strictly to your visual identity.
Applications of LoRA Technology
LoRA solves the "randomness" problem of generative AI, allowing for precise control over the subject matter.
Character Consistency
Train a LoRA on 15-20 photos of a specific person or character. Every future generation with the trigger word produces that exact face and likeness, solving the "randomness" problem of generative AI. Perfect for brand mascots, virtual influencers, and storytelling with consistent characters across scenes.
Brand Style Enforcement
Feed 20-50 images of your brand's visual identity. The LoRA learns your color palettes, composition rules, and design language. All future generations automatically conform to your brand guidelines — no manual style matching required. Works with FLUX and SDXL base models.
Product Photography
Train on 10-15 clean product shots from different angles. Generate unlimited lifestyle images, colorways, and marketing visuals of the exact same product. Best for e-commerce catalogs and social media content at scale. See also our Best Open Source Image Models for base model options.
The LoRA Workflow
From raw images to consistent generation in three steps.
1
Dataset Preparation
Upload 10-20 high-quality images of your subject (character, object, or style). Caption them accurately to help the AI understand what to learn.
2
Efficient Training
WaveSpeed's infrastructure handles the training process. Unlike full model training which takes days, LoRA training focuses on specific layers and completes in minutes to an hour at a fraction of the cost.
3
Triggered Generation
Once trained, the LoRA is a small file (10MB - 300MB). To generate, simply include the Trigger Word (e.g.,
<lora:my-brand-style:1.0>) in your prompt. The base model (e.g., FLUX.1) will instantly shift its output to match your trained concept.Q & A
What is the difference between a Checkpoint and a LoRA?
A Checkpoint (like SDXL) is a massive file (GBs) representing the entire brain of the AI. A LoRA is a small adapter file (MBs) that fine-tunes a specific part of that brain. LoRAs are faster to train, easier to share, and can be swapped instantly without reloading the main model.
Can I use multiple LoRAs at once?
Yes. WaveSpeed supports Multi-LoRA mixing. You can combine a "Character LoRA" with a "Style LoRA" and a "Clothing LoRA" in a single prompt to generate your specific character, wearing your specific clothes, in your specific art style.
Which base models support LoRA generation?
We support LoRA generation for all major foundation models, including the entire FLUX.1 family, Stable Diffusion XL (SDXL), and Stable Diffusion 1.5.
How many images do I need to train a LoRA?
For a specific style, 20-50 images are recommended. For a specific face or character, 15-20 high-quality, varied photos are usually sufficient. For a specific object, 10-15 clean images from different angles work best.
Do I own the LoRA model I train?
Yes. Models trained on your private data within your WaveSpeed workspace are your intellectual property. You can choose to keep them private or publish them to the community library.