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BackGwa/Character-LoRA
Character-LoRA is a text-to-image model from BackGwa. Use it when you need an image from a text prompt. The card lists the license as creativeml-openrail-m.
Character-LoRA is an SDXL-based character LoRA created to reproduce the BACKGWA character using a copyright-conscious synthetic image dataset.
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Updated May 13, 2026
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From the Hugging Face model README
Character-LoRA is an SDXL-based character LoRA created to reproduce the BACKGWA character using a copyright-conscious synthetic image dataset.
This LoRA was developed as part of research on whether a character LoRA can be trained without directly using original character images or artist-created works as training data.
Instead of collecting or reusing human-made artwork, the training dataset was constructed from AI-generated synthetic images based on structured character descriptions.
The full research document, methodology, instruction template, and JSON schema are available in the GitHub repository: BackGwa/Character-LoRA
Through this approach, the research examines a workflow for constructing character LoRA models while reducing dependence on original images and considering copyright, training rights, artistic style, and intellectual property.
Use the trigger word below to activate the BACKGWA character.
You can add extra prompts for outfit, expression, pose, background, or composition as needed.
backgwa
This LoRA was designed for use with SDXL-based model environments.
For the most stable and consistent results, it is recommended to use it with the LUMIERE-Q model, though it may also be used with other SDXL-compatible checkpoints.
This LoRA was trained without using artist-created images or human-made artwork as training data.
The dataset was generated with GPT Image 2.
A total of 80 synthetic images were generated as training candidates, and 48 images were selected for the final dataset based on consistency and quality.
To prepare the character description used for image generation, the original character image and supplementary information were provided to the locally executed gemma-4-E4B-it model.
The analysis used predefined instructions and a structured JSON schema to describe the character in a form suitable for subsequent synthetic image generation.
The selected synthetic images were then labeled using GPT-5.5.
The labels describe visible attributes such as expression, pose, composition, and other image-specific details used during training.
The LoRA was trained using sd-scripts on the SDXL-based LUMIERE-Q model.
| Parameter | Setting |
|---|---|
| Base Model | LUMIERE-Q |
| Dataset Size | 48 images |
| Epochs | 10 |
| Repeats | 10 |
| Resolution | 1024x1024 |
The research document and related materials are available at: BackGwa/Character-LoRA
The LoRA model is released under the CreativeML Open RAIL-M license.
The research document and repository materials are released under the MIT License, unless otherwise specified.