LAXMAYDAY/Anima_Tile_and_Repair_ControlNet-LLLite

Anima Tile & Repair ControlNet-LLLite

This repository contains the first public release of Anima Tile & Repair ControlNet-LLLite, a lightweight ControlNet-LLLite model for the Anima image model family.

The model is intended for anime image repair workflows. It is designed to provide tile/repair-style guidance for improving anime images affected by visible noise, blur, compression artifacts, or low-detail degradation, while keeping the original composition and character structure stable.

This is a v1 release. Future updates are planned.

Files

File	Description
anima_tiled_lllite_v1.safetensors	Recommended v1 checkpoint.
anima_tiled_lllite_v1-000002.safetensors	Earlier training checkpoint.
anima_tiled_lllite_v1-000004.safetensors	Earlier training checkpoint.
anima_tiled_lllite_v1-000006.safetensors	Earlier training checkpoint.
anima_tiled_lllite_v1-000008.safetensors	Later training checkpoint before final export.

Intended Use

Use this model as a ControlNet-LLLite guidance module together with an Anima-compatible generation or restoration workflow.

Typical use cases:

• repairing noisy anime images;
• reducing blur and softness;
• improving tiled/local detail consistency;
• restoring degraded anime-style images while preserving layout and character structure.

Usage Notes

The anima-edit project documentation describes ControlNet-LLLite as a lightweight alternative to ControlNet. Relevant inference options include:

• --control_net_lllite_models: path to the ControlNet-LLLite model file;
• --control_net_multipliers: guidance strength / multiplier;
• --control_net_ratios: step ratio during which ControlNet-LLLite is applied.

ControlNet and ControlNet-LLLite should not be used at the same time in the same workflow.

Example path usage:

--control_net_lllite_models /path/to/anima_tiled_lllite_v1.safetensors \
--control_net_multipliers 1.0 \
--control_net_ratios 1.0

The exact strength depends on the base Anima checkpoint, sampler, resolution, denoise strength, and the severity of the degradation. For a first test, start with a moderate multiplier and adjust upward only if the repair guidance is too weak.

Compatibility

This release is intended for Anima-based anime image restoration workflows and was prepared in the anima-edit ecosystem.

Anima uses a DiT-style architecture with a Qwen3 text encoder / adapter stack and Qwen-Image VAE components. This ControlNet-LLLite checkpoint is not a standalone image model; it must be loaded as an auxiliary guidance model in a compatible workflow.

Limitations

• This is an early v1 release.
• It is focused on anime image repair, not general photographic restoration.
• Strong guidance may alter fine details or over-sharpen images.
• Results depend heavily on the base Anima model and the surrounding inference pipeline.

Release Notes

v1

Initial release of Anima Tile & Repair ControlNet-LLLite for anime denoising, deblurring, and tiled repair guidance.

Future versions may include improved robustness, more training data, and updated checkpoints.