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BackGwa/Character-LoRA-Anima
Character-LoRA-Anima 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 other.
This research extends the Character-LoRA project based on the Anima model, focusing on research and testing with the BACKGWA character. The original SDXL-based model is Character-LoRA (BACKGWA), and the related resear…
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Updated May 22, 2026
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From the Hugging Face model README
This research extends the Character-LoRA project based on the Anima model, focusing on research and testing with the BACKGWA character. The original SDXL-based model is Character-LoRA (BACKGWA), and the related research repository is BackGwa/Character-LoRA.
Please note that Anima differs from the original research in several aspects, including dataset labeling, training configuration, and other setup details. Therefore, this repository and model should be understood as a separate Anima-based research and testing project, rather than a direct continuation of the original SDXL-based model.
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 Anima-based model environments.
For the most stable and consistent results, it is recommended to use it with the anima-base-v1.0 model.
This model is not the result of a single standalone training run. It was produced through dataset reconstruction, multiple experimental training runs, LoRA/checkpoint merging, and additional fine-tuning. Therefore, the dataset size, epoch count, and training settings below are provided as references for the research process, and the final model metadata may not fully represent the entire training history.
| Parameter | Setting |
|---|---|
| Base Model | anima-base-v1.0 |
| Resolution | 1024x1024 |
| Initial Learning Rate | 1e-5 |
| Initial Training | 40 epochs, 40th epoch used |
| Additional Learning Rate | 2e-5 |
| Additional Training | 20 epochs, 10th epoch used |
| Additional Dataset Size | 19 images |
The main training dataset was organized into three subsets:
| Dataset | Size | Repeat | Purpose |
|---|---|---|---|
backgwa_base | 40 images | 2x per epoch | Learns the character’s core appearance and basic features while reducing excessive bias toward specific poses or expressions. |
backgwa_alignment | 20 images | 4x per epoch | Preserves the character’s invariant identity and reduces bias introduced by backgwa_additional and earlier Release 1 behavior. |
backgwa_additional | 40 images | 1x per epoch | A dataset for improving expressiveness and prompt responsiveness under various transformation conditions, including body type, age, clothing coverage, and detailed visual depiction. |
The dataset was rebuilt using selected images from previous datasets based on quality and suitability, along with images generated using the Release 1 model. The overall style distribution was adjusted to reduce overfitting to a fixed visual style. Specific artist names were not directly used when creating the dataset, in order to avoid explicitly relying on a particular artist’s style.
During the research process, several dataset and training configurations were tested, including larger reconstructed datasets, stricter labeling, removing or rebalancing backgwa_additional, and splitting the dataset into separate subsets with adjusted repeat counts. These experiments produced partial improvements, but did not fully resolve style bias, prompt-response instability, or character reproduction issues.
For the final approach, multiple LoRAs and checkpoints were selected and merged. A total of 5 models were used in the merge, including Research Preview, Release 1, and two checkpoints from the Release 2 research process. The merged model showed better results than Research Preview, Release 1, and the intermediate experimental models. To reduce remaining issues inherited from Release 1, the merged LoRA was further trained using a dedicated 19-image dataset with a learning rate of 2e-5. This additional training was run for 20 epochs, and the 10th epoch result was used.
The research document and related materials are available at: BackGwa/Character-LoRA
The LoRA model is released under the circlestone-labs-non-commercial-license.
The research document and repository materials are released under the MIT License, unless otherwise specified.