Instructions to use mlx-community/moge-3-vitl-mlx-fp32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/moge-3-vitl-mlx-fp32 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download mlx-community/moge-3-vitl-mlx-fp32 --local-dir moge-3-vitl-mlx-fp32
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Store ConvTranspose2d weights in MLX (out, kh, kw, in) layout
Browse filesRelayout of the 12 `*.resamplers.N.0.weight` tensors from torch (in, out, 2, 2) to MLX (out, 2, 2, in) so mlx-vlm loads them directly into nn.ConvTranspose2d without transposing at load time. All other tensors are byte-identical; model outputs are unchanged.
- model.safetensors +2 -2
model.safetensors
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