Instructions to use SceneWorks/boogu-image-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use SceneWorks/boogu-image-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir boogu-image-mlx SceneWorks/boogu-image-mlx
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
| license: apache-2.0 | |
| base_model: | |
| - Boogu/Boogu-Image-0.1-Base | |
| - Boogu/Boogu-Image-0.1-Turbo | |
| - Boogu/Boogu-Image-0.1-Edit | |
| pipeline_tag: text-to-image | |
| tags: | |
| - mlx | |
| - apple-silicon | |
| - text-to-image | |
| - image-editing | |
| - boogu-image | |
| library_name: mlx-gen | |
| # Boogu-Image-0.1 β native MLX | |
| Pre-converted, native **MLX** weights of [Boogu-Image-0.1](https://huggingface.co/Boogu) for Apple | |
| Silicon, loaded by [SceneWorks](https://sceneworks.io)' `mlx-gen` Rust engine β no PyTorch / Python at | |
| inference. Boogu is a Lumina-Image-2.0 / OmniGen2-lineage flow-matching image model: a mixed | |
| single/double-stream DiT (~10.3B) + a Qwen3-VL-8B condition encoder + the FLUX.1 16-channel VAE. | |
| ## Variants | |
| Each subfolder is a complete snapshot β `transformer/` (DiT) + `mllm/` (Qwen3-VL encoder + tokenizer) | |
| + `vae/` β loadable directly. | |
| | Folder | Source | Task | | |
| |---|---|---| | |
| | `base/` | Boogu-Image-0.1-Base | text-to-image (true-CFG) | | |
| | `turbo/` | Boogu-Image-0.1-Turbo | text-to-image (DMD few-step, no CFG) | | |
| | `edit/` | Boogu-Image-0.1-Edit | reference image + instruction β edited image | | |
| | `base-bf16/` `turbo-bf16/` `edit-bf16/` | (above) | same models, **full precision** | | |
| The bare-named folders are the **default Q8** build; the `-bf16` folders are the unquantized originals | |
| for maximum quality / experimentation. | |
| ## Quantization (Q8 folders) | |
| Group-wise affine **Q8, group size 32** β the DiT hidden size (3360) is divisible by 32, not the usual | |
| 64. Quantized: the DiT Linears + the Qwen3-VL **text-tower** Linears. Kept full precision: the FLUX.1 | |
| VAE (decode-precision-sensitive), the Qwen3-VL **vision tower** (runs f32), and the token-embedding | |
| table. | |
| Footprint (measured @ 1024Β²): Q8 ~35.5 GB peak β recommended **64 GB** Mac. (Q4 would be ~27β30 GB / | |
| 48 GB; not shipped here.) bf16 runs require more. | |
| ## Usage | |
| Loaded by `mlx-gen-boogu` via `BooguPipeline::from_snapshot("<variant folder>")` (text-to-image, | |
| Turbo few-step, and single-reference image edit). Used by SceneWorks Image Studio. | |
| ## License | |
| **Apache-2.0**, inherited from the upstream `Boogu/Boogu-Image-0.1-{Base,Turbo,Edit}` checkpoints. | |
| These are re-quantized/repackaged copies of those weights for MLX; all credit to the Boogu authors. | |