Fine-tuning pipeline for brand-specific video style

[Stanley-blik]

Overview

Allow users to fine-tune Wan 2.2 on their own video/image dataset to create a consistent brand-specific visual style.

Tasks

• LoRA fine-tuning script for Wan 2.2
• Dataset preparation tools (video → frame extraction → caption generation)
• Training configuration (learning rate, steps, rank)
• LoRA loading in inference server
• Multiple LoRA support (swap styles per video)
• Documentation: how to fine-tune for your brand

Use Cases

• Consistent animation style across all Toons content
• Brand-specific color grading and cinematography
• Character-specific LoRAs for perfect consistency

References

• HuggingFace video dataset scripts
• Fine-tuning open video generators for cinematic synthesis

Acceptance Criteria

• Can fine-tune Wan 2.2 with a LoRA on custom dataset
• LoRA loads at inference time without full model reload
• Visible style difference between base and fine-tuned model