Instructions to use darask0/anima-distill-loras with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use darask0/anima-distill-loras with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("circlestone-labs/Anima", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("darask0/anima-distill-loras") 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
Upload README.md with huggingface_hub
Browse files
README.md
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---
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license: apache-2.0
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base_model: circlestone-labs/Anima
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tags:
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- lora
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- distillation
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- anime
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- text-to-image
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- anima
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library_name: diffusers
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---
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# Anima Distillation LoRAs
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[CircleStone Labs / Anima v1.0](https://huggingface.co/circlestone-labs/Anima)
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(2B パラメータ DiT、Cosmos-Predict2 派生) 用の **蒸留 LoRA コレクション**。
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4-step / CFG=1.0 で teacher 品質に近づける各手法を順次追加していく。
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## Available LoRAs
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| サブディレクトリ | 手法 | 推奨 step / CFG | 詳細 |
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|---|---|---|---|
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| [`pcm/`](pcm) | Phased Consistency Model | 4-step / CFG=1.0 | [pcm/README.md](pcm/README.md) |
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将来追加予定 (進捗あり次第): LADD / Reflow / Z-Image trajectory / DMD2 など。
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## File Formats
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各サブディレクトリには **2 種類のフォーマット**で同じ重みを配布:
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| 拡張子 | 用途 |
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|---|---|
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| `*_peft.safetensors` | PEFT (diffusers) — 自前推論スクリプト、`peft` library |
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| `*_comfy.safetensors` | ComfyUI — `LoraLoaderModelOnly` で直接ロード可 |
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## ComfyUI 最短手順
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1. `pcm/pcm_final_comfy.safetensors` を `ComfyUI/models/loras/` に配置
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2. Anima v1.0 base workflow に `LoraLoaderModelOnly` を挿入、`strength_model: 1.0`
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3. KSampler を設定:
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- **steps: 4**
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- **cfg: 1.0**
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- sampler / scheduler: `er_sde + simple` (softer、生成 8.8s) または
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`res_multistep + beta` (anime style 強め、生成 11.2s)
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4. `ModelSamplingAuraFlow` で `sigma_shift: 3.0` (base 公式推奨)
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詳細な使い方・訓練ハイパーパラメータは各サブディレクトリの `README.md` を参照。
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## Sample (PCM, step 4000 + res_multistep + beta)
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Prompt: `2girls, flandre scarlet, remilia scarlet, touhou, ...`
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4-step CFG=1.0、Anima v1.0 base、seed 42。
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## Source / Training Pipeline
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訓練コード・データセット生成・Modal 実装一式:
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[github 不要、HF を主とした自前リポジトリ](https://github.com/) — 詳細は近日中に
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コードを公開予定。
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## License
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- 本リポジトリの **LoRA 重み**: Apache-2.0
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- **Base model (Anima v1.0)** には別途以下のライセンスが適用される (派生モデルも縛り受ける):
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- CircleStone Labs Non-Commercial License
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- NVIDIA Open Model License (Derivative Model 条項)
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- **非商用利用のみ可能**。商用利用は Anima 公式に問い合わせ:
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[circlestone-labs/Anima](https://huggingface.co/circlestone-labs/Anima)
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## References
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- PCM 元論文: [Wang et al. NeurIPS 2024](https://arxiv.org/abs/2405.18407)
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- PCM 公式実装: [G-U-N/Phased-Consistency-Model](https://github.com/G-U-N/Phased-Consistency-Model)
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- Anima base: [circlestone-labs/Anima](https://huggingface.co/circlestone-labs/Anima)
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