Training Tools — Fine-Tune Custom AI Models in the Cloud
Customize AI models with your own data. WaveSpeed provides powerful cloud-based training tools to fine-tune foundation models like FLUX.1 and Stable Diffusion — no GPU required.
The Model Training Process
From raw images to a deployable custom model in four simple steps. Upload your dataset, configure training, and deploy — all through a single API.
Cloud-Powered Processing
No GPU required. Send a request and get results through our optimized cloud infrastructure. All training happens on WaveSpeed servers so you can start a job from a laptop or tablet.
Developer-Friendly API
Simple REST endpoints with Python and JavaScript SDKs. Integrate custom model training into any workflow in minutes with comprehensive documentation.
Production-Ready Output
Train high-quality LoRAs and checkpoints suitable for commercial use. Consistent performance at scale with FLUX.1 and SDXL base models.
Training on WaveSpeed vs. Self-Hosted Infrastructure
See why teams choose WaveSpeed Training Tools over self-hosted alternatives.
Performance at a Glance
Train custom LoRAs and checkpoints on WaveSpeed cloud infrastructure.
Examples
Young woman turning to smile at camera, breeze catching her scarf, soft bokeh background.
Dancer performing a graceful pirouette, flowing dress creating motion trails, spotlight.
Butterfly emerging from chrysalis in close-up, wings slowly unfurling, soft natural light.
Detective walking through foggy city streets, trench coat collar up, film noir atmosphere.
Integrate in Minutes
Production-ready SDKs for Python and JavaScript. REST API with full OpenAPI spec. Webhook support for async jobs.
- Train LoRAs on FLUX.1 and SDXL
- Upload datasets via URL or direct upload
- Python & JavaScript SDKs + REST API
Get Any Tool You Want
1000+ models across image, video, audio, and 3D — all through one API.
FAQ
No. All training happens on WaveSpeed's cloud infrastructure. You can start a training job from a laptop or even a tablet; our servers handle the heavy lifting.
LoRA (Low-Rank Adaptation) is a faster, more efficient method that creates a small "adapter" file (MBs) to work with a base model. Full Fine-tuning updates the entire model (GBs). For most users, LoRA offers the best balance of quality and flexibility.
For a LoRA, we recommend 15-20 high-quality images for a face or object, and 30-50 images for a style. Quality matters more than quantity—ensure your images are clear and well-lit.
Yes. We support FLUX.1 LoRA training. This allows for incredibly high-fidelity results, especially for photorealistic characters and text rendering.
Yes. Your uploaded datasets and the resulting trained models are private to your account by default. We do not use your private data to train our public foundation models.