Instructions to use masafy/masafee-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use masafy/masafee-lora with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("gsdf/Counterfeit-V3.0", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("masafy/masafee-lora") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Add Zenodo DOI badge and citation entry
Browse files
README.md
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# Masafee LoRA
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Stable Diffusion LoRA for the original character **Masafee** — a red panda from a personal [LINE sticker set](https://store.line.me/stickershop/product/19794926/ja).
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Trained entirely on a single consumer GPU (NVIDIA GeForce RTX 3060, 12GB) with [kohya-ss/sd-scripts](https://github.com/kohya-ss/sd-scripts).
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2. **Epoch ~30 is the sweet spot** — extending to 40–60 epochs produced visible overfitting without improving character fidelity.
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3. **Output quality is bounded by training image count** — with only 13 stickers, certain poses and lighting conditions remain out of distribution.
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## License
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- **LoRA weights (this file):** released for **personal and research use only**. The weights encode a specific copyrighted character.
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By downloading this model you agree to use it only for personal experimentation or academic research.
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## Citation
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If you reference this work, please link the GitHub repository above. A Zenodo DOI is planned.
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---
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Made with 🐾 by [masafykun](https://github.com/masafykun) · [masafy.org](https://masafy.org/)
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# Masafee LoRA
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[](https://github.com/masafykun/masafee-lora)
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[](https://doi.org/10.5281/zenodo.20397946)
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[](https://orcid.org/0009-0000-7977-2756)
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Stable Diffusion LoRA for the original character **Masafee** — a red panda from a personal [LINE sticker set](https://store.line.me/stickershop/product/19794926/ja).
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Trained entirely on a single consumer GPU (NVIDIA GeForce RTX 3060, 12GB) with [kohya-ss/sd-scripts](https://github.com/kohya-ss/sd-scripts).
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2. **Epoch ~30 is the sweet spot** — extending to 40–60 epochs produced visible overfitting without improving character fidelity.
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3. **Output quality is bounded by training image count** — with only 13 stickers, certain poses and lighting conditions remain out of distribution.
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## Citation
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If you use this model in academic work, please cite it via the Zenodo archive:
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```bibtex
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@software{suzuki_masafee_lora_2026,
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author = {Suzuki, Masato},
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title = {{Masafee LoRA: Single-GPU LoRA Fine-tuning of an
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Original Character on Stable Diffusion}},
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year = {2026},
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version = {v1.0.0},
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doi = {10.5281/zenodo.20397946},
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url = {https://doi.org/10.5281/zenodo.20397946},
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orcid = {0009-0000-7977-2756}
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}
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```
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**Persistent archive (Zenodo DOI):** [10.5281/zenodo.20397946](https://doi.org/10.5281/zenodo.20397946)
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## License
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- **LoRA weights (this file):** released for **personal and research use only**. The weights encode a specific copyrighted character.
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By downloading this model you agree to use it only for personal experimentation or academic research.
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---
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Made with 🐾 by [masafykun](https://github.com/masafykun) · [masafy.org](https://masafy.org/) · [ORCID](https://orcid.org/0009-0000-7977-2756)
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