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Raelina/Raejin-Anima

sourceHugging Faceotherupdated 6mo agoView on Hugging Face
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<div class="container"> <div class="title-container"> <div class="title"><span>Raejin Anima</span></div> </div> <div class="gallery"> <img src="https://cdn-uploads.huggingface.co/production/uploads/64b24543eec33e27dc9a6eca/To-K1S6lKzVC60Nh8_J.png" alt="Image 1"> <img src="https://cdn-uploads.huggingface.co/production/uploads/64b24543eec33e27dc9a6eca/Ku5fvIDEoEkfXaJ25Sjjk.png" alt="Image 2"> <img src="https://cdn-uploads.huggingface.co/production/uploads/64b24543eec33e27dc9a6eca/qUpk0SF2BiKbVyt8vCQZX.png" alt="Image 3"> <img src="https://cdn-uploads.huggingface.co/production/uploads/64b24543eec33e27dc9a6eca/K4p1kVmS33DBtC8M1tf-l.png" alt="Image 4"> </div> </div>

Overview

Raejin Anima is a specialized fine-tune of the Anima base model, meticulously crafted to elevate its visual fidelity. This model addresses specific limitations found in the original, aiming to deliver a more polished, aesthetic, and balanced output while preserving the core strengths of the base model.

Model Details

  • —Developed by: Raelina
  • —Model type: Diffusion-based text-to-image generative model
  • —Finetuned from: Anima
  • —Prompt style: Booru-style tags and Natural Language

Training Details

v0.1 (Experimental Alpha)

  • —Base Model: anima-preview2
  • —Method: Full fine-tuning using the kohya/sd-scripts trainer.
  • —Stability: LLM Adapter was disabled during training to mitigate catastrophic forgetting, ensuring the model retains its foundational knowledge while adopting new stylistic improvements.
  • —Dataset: Trained on a curated set of 2,2k high-quality images, utilizing a hybrid captioning strategy of both booru-style tags and natural language to enhance prompt adherence and stylistic depth.

Recommended settings

  • —Positive prompts:
masterpiece, best quality, absurdres
  • —Negative prompts:
low quality, worst quality, jpeg artifacts, bad anatomy, bad hands, bad proportions, mutation, deformed, extra digits, fewer digits, missing arms, missing legs, signature, watermark, username
  • —CFG: 4-5
  • —Sampling steps: 30-50
  • —Sampler: Euler a or ER SDE
  • —Scheduled type: Normal
  • —Standard Resolution:
832 x 1216, 1216 x 832, 1152 x 896, 896 x 1152, 1344 x 768, 768 x 1344, 1024 x 1024

Acknowledgements

A special thanks to the community and the developers who made this project possible:

  • —Circlestone Labs: For providing the incredible open-source Anima base model.
  • —Kohya_ss & Contributors: For the comprehensive and powerful open-source training framework

Support

If you’d like to support this project or my other developments, you can buy me a coffee on Ko-Fi

License

CircleStone Labs Non-Commercial License