Instructions to use xocialize/anima-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use xocialize/anima-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir anima-mlx xocialize/anima-mlx
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
| license: other | |
| license_name: circlestone-noncommercial | |
| license_link: LICENSE | |
| library_name: mlx | |
| pipeline_tag: text-to-image | |
| tags: | |
| - mlx | |
| - apple-silicon | |
| - text-to-image | |
| - anime | |
| - cosmos-predict2 | |
| base_model: | |
| - circlestone-labs/Anima | |
| # Anima-MLX β anime text-to-image for Apple Silicon (MLX) | |
| Pure-[MLX](https://github.com/ml-explore/mlx) port of **[circlestone-labs/Anima](https://huggingface.co/circlestone-labs/Anima)**, | |
| an anime/illustration text-to-image model. The denoiser is **NVIDIA Cosmos-Predict2-2B** | |
| (`CosmosTransformer3DModel`); the text path is **Qwen3-0.6B β a 6-block `llm_adapter`**; the | |
| decoder is the **Qwen-Image / Wan 16-channel 3D-causal VAE**. | |
| > **Built on NVIDIA Cosmos.** The base denoiser is licensed under the NVIDIA Cosmos Open Model | |
| > License. The Anima fine-tune weights are **Non-Commercial** (CircleStone Labs). This MLX port is | |
| > redistributed under the same Non-Commercial terms β **personal / research use only, not for | |
| > commercial use.** Port code: MIT. | |
| ## Parity | |
| Every component is parity-locked against a PyTorch oracle, and the full pipeline against a torch | |
| reference (injected noise + identical token ids): | |
| | stage | metric | | |
| |---|---| | |
| | Cosmos DiT | fp32 max_abs 3.1e-5 Β· bf16/GPU cos 0.999995 | | |
| | llm_adapter | fp32 max_abs 2.9e-5 Β· bf16/GPU cos 0.999995 | | |
| | Qwen3-0.6B TE | fp32 max_abs 6.1e-4 Β· bf16/GPU cos 0.999998 | | |
| | Wan/Qwen-Image VAE | fp32 max_abs 7.5e-6 Β· bf16/GPU cos 0.999954 | | |
| | e2e (text path) | max_abs 2.3e-6 | | |
| | e2e (DiT-in-loop + CFG, step 0) | cos 1.0000000 | | |
| | transformer int8 g128 | per-pass cos 0.99991 | | |
| | transformer int4 g64 | per-pass cos 0.99628 | | |
| ## Files | |
| | file | dtype | resident | | |
| |---|---|---| | |
| | `transformer-bf16.safetensors` | bf16 | 3.91 GB | | |
| | `transformer-int4.safetensors` | int4 (attn+ff, g64) | 1.38 GB | | |
| | `llm_adapter-bf16.safetensors` | bf16 | ~0.24 GB | | |
| | `text_encoder-bf16.safetensors` | bf16 | ~1.2 GB | | |
| | `vae-bf16.safetensors` | bf16 | ~0.25 GB | | |
| Measured peak unified memory @512Β²: ~14 GB (bf16) / ~6 GB (int4 transformer). | |
| ## Sampling | |
| ComfyUI `ModelType.FLOW` β `CONST` prediction + `ModelSamplingDiscreteFlow(shift=3, multiplier=1)`: | |
| `sigma(t) = 3t / (1 + 2t)`, **DiT timestep == sigma β [0,1]**, Wan21 latent denorm before decode. | |
| CFG 4β5. Tokenizers: Qwen2.5 (raw BPE, pad 151643) + T5-v1.1 SentencePiece (32128, trailing eos). | |
| ## Credits | |
| - Anima β CircleStone Labs (Non-Commercial) | |
| - Cosmos-Predict2 β NVIDIA (Cosmos Open Model License) | |
| - Qwen3 β Alibaba Β· Wan VAE β Alibaba/Wan | |
| - MLX port β xocialize | |