Train a character LoRA
Fine-tune a LoRA on a specific character (original IP, illustrated, or photoreal) so it can be reproduced consistently across poses and scenes.
Estimated $2–$9 per training run · 15–45 min
What inputs you need
- 15–40 character reference images (varied poses/angles)
- Character-focused captions
- Training config
What Badgr returns
- Trained character LoRA
- Training loss curve
- Sample generations across poses
Recommended GPU routes
Estimated cost: $2–$9 per training run · Estimated runtime: 15–45 min
Example command
badgr run "python train_lora.py --config character_lora.yaml" \
--gpu A100_40GB \
--max-cost 9 \
--max-runtime 60Common setup failures Badgr avoids
Character identity drift across poses at inference time — training config enforces a minimum pose-variety threshold in the input set before starting.
Sample generations look like the reference pose instead of generalizing — the training set is checked for angle/expression variety before the run starts.
Ready to run this?
Launch from the dashboard, CLI, or Compute API. Max-cost protection included.