Model Name: Impasto Anime Style (Anima Edition) v0.5-MQ

Style: Impasto / Painterly

Compatible Base Model: Anima Base (circlestone-labs/Anima)

This LoRA represents a significant evolution from the previous Z-Image-Turbo version, now trained on the Anima Base architecture using firdosi/diffusion-pipe. The dataset has been massively expanded to 11.3k images, curating thick-paint (impasto-style) fan artworks across multiple titles including Genshin Impact, Honkai: Star Rail, Zenless Zone Zero, and Blue Archive.

As with the initial release, the training focus remains strictly on capturing distinctive painterly textures and brushwork rather than character fidelity. Character identities were not labeled or tagged during training; this model is an experimental attempt to generalize the impasto aesthetic across a broader range of anime-style source material.

Usage Recommendations:

* LoRA Weight: 0.3 – 1.2 (Recommended starting point due to the larger dataset and higher rank)

* Prompting: Use natural language descriptions directly. The model responds well to intuitive prompts describing texture (e.g., "thick oil paint," "visible brushstrokes," "impasto style").

Disclaimer: This model was trained on publicly available fan-created content and is intended strictly for personal, non-commercial use.

Training Details:

* Toolkit: firdosi/diffusion-pipe

* Base Model: Anima Base

* Dataset Size: 11.3k images (Multi-game: Genshin, HSR, ZZZ, Blue Archive...)

* Captioning: Qwen3.5 + manual correction]

* Steps: 1,313

* Batch Size: 8

* Rank: 16

* Learning Rate: 3e-5

Model Name: Impasto Anime Style (ZIT Edition) v0.1-HO

Style: Impasto

Compatible Base Model: Z-Image-Turbo

This LoRA was trained on a curated set of ~150 thick-paint (impasto-style) Genshin Impact fan artworks from Pixiv. The training images were selected for their distinctive painterly texture and brushwork. Note that character identities were not labeled or tagged during training—this is primarily an experimental attempt focused on capturing artistic style rather than character fidelity.

Usage Recommendations:

• LoRA Weight: 0.8 – 1.0

• Prompting: Use natural language descriptions directly. (Note: Training captions were structured Chinese phrases, but the model responds well to intuitive prompts.)

Disclaimer: This model was trained on publicly available fan-created content and is intended strictly for personal, non-commercial use.

Training Details:

• Toolkit: Ostris AI Toolkit

• Captioning: Qwen3-VL + manual correction

• Image resolution: 256–512px

• Steps: 1,350

• Rank: 4

• Learning rate: 5e-4