How to Train Z-Image Turbo LoRA on Fal.ai
Z-Image Turbo LoRA Trainer is a cloud training service by fal.ai, allowing you to fine-tune high-quality models quickly without local GPUs.
Core Training Steps
1. Preparation
Register on fal.ai and get API credits. New users often get trial credits. Single LoRA training usually costs $2-5.
2. Prepare Dataset
Select 15-50 HD images (1024x1024 recommended), ensure clarity and consistent style, then pack into a ZIP file.
3. Configuration
4. Generate & Integrate
Click train and wait. Preview or download weights directly on fal cloud when done. Recommended weight: 0.7 to 1.0 for best results.
Cloud vs Local Training
| Item | Fal.ai Cloud | Local Env |
|---|---|---|
| Setup Cost | Very Low (Browser only) | High (GPU & Python) |
| Hardware | High-perf A100/H100 | Requires GPU (24GB VRAM+) |
| Target User | Efficiency seekers | Enthusiasts, Deep customization |
Common Questions
LoRA effect not obvious?
Check if Prompt includes trigger word, try increasing strength. Ensure training steps are 1500+.
Severe distortion?
Usually a sign of "Overfitting". Try reducing training steps or lowering generation weight scale.
Images look blurry?
Check original dataset quality. Recommend 1024px+, no watermarks, simple composition.
Upload always fails?
Check if ZIP file is corrupted, ensure images are in root directory, total size under 300MB.
Advanced: Identify & Fix Overfitting
Overfitting is like the model "memorizing" answers. It remembers every detail of training images but loses the ability to understand and create new scenes.
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