Instructions to use ddalcu/TRELLIS.2-4B-MLX-Serve-8bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use ddalcu/TRELLIS.2-4B-MLX-Serve-8bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download ddalcu/TRELLIS.2-4B-MLX-Serve-8bit --local-dir TRELLIS.2-4B-MLX-Serve-8bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
TRELLIS.2-4B for mlx-serve (8-bit)
microsoft/TRELLIS.2-4B repackaged for mlx-serve on Apple Silicon. Microsoft's image-to-3D model: an image with a transparent background becomes a textured PBR GLB.
- The flow-model (DiT) block projections are affine-quantized to 8 bit, group size 64; everything else is as released.
- Includes the DINOv3 image encoder it conditions on (float16); its licence is in
dinov3/LICENSE.md. - No background remover is included: send an image with a transparent background (alpha is the subject).
Licences
The TRELLIS.2-4B weights are MIT (LICENSE). The bundled DINOv3 encoder is Meta's, under the DINOv3 License
(dinov3/LICENSE.md), which travels with any redistribution of it.
Run: mlx-serve --model-dir <folder holding this repo>, then POST /v1/3d/generations.
Converted by tests/convert_trellis2_pixal3d.py in the mlx-serve repository.
Hardware compatibility
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Base model
microsoft/TRELLIS.2-4B