Instructions to use mlx-community/sam-3d-objects-bf16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/sam-3d-objects-bf16 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir sam-3d-objects-bf16 mlx-community/sam-3d-objects-bf16
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
| { | |
| "mlx_version": "0.32.2", | |
| "tensor_count": 3895, | |
| "parameter_elements": 3530447862, | |
| "weight_bytes": 7801464522, | |
| "dtypes": { | |
| "sam": { | |
| "bfloat16": 3288 | |
| }, | |
| "depth_model": { | |
| "float32": 607 | |
| } | |
| }, | |
| "strict_load": { | |
| "missing": 0, | |
| "extra": 0, | |
| "shape_mismatches": 0 | |
| }, | |
| "trainable_tensors": 0, | |
| "regression_tests": { | |
| "class": "TestSAM3DObjects", | |
| "passed": 17 | |
| }, | |
| "reference_comparison": { | |
| "precision": "float32", | |
| "mlx_device": "CPU", | |
| "reference": "Original PyTorch source; CPU adapter for the unavailable spconv backend", | |
| "maximum_absolute_errors": { | |
| "attention_False": 1.1920928955078125e-07, | |
| "attention_True": 1.1920928955078125e-07, | |
| "resize_False_False": 2.384185791015625e-07, | |
| "resize_False_True": 1.430511474609375e-06, | |
| "resize_True_False": 3.5762786865234375e-07, | |
| "resize_True_True": 9.5367431640625e-07, | |
| "structure_6drotation_normalized": 1.1920928955078125e-07, | |
| "structure_scale": 4.76837158203125e-07, | |
| "structure_shape": 4.76837158203125e-07, | |
| "structure_translation": 1.1920928955078125e-07, | |
| "structure_translation_scale": 2.9802322387695312e-08, | |
| "occupancy_decoder": 1.6391277313232422e-06, | |
| "sparse_latent_flow": 2.942979335784912e-07, | |
| "flexicubes_vertices": 2.9802322387695312e-08, | |
| "flexicubes_colors": 1.1920928955078125e-07, | |
| "flexicubes_faces": 0.0 | |
| } | |
| }, | |
| "depth_model": { | |
| "source": "mlx-community/moge-3-vitl-mlx-fp32", | |
| "base": "Ruicheng/moge-3-vitl", | |
| "validation": "MoGe-3 MLX port validated against the PyTorch reference in mlx-vlm (CPU float32): identical valid-pixel masks and under 0.2% median relative depth error" | |
| }, | |
| "benchmark": { | |
| "hardware": "Apple M5 Max, 128 GiB unified memory", | |
| "dtype": "bfloat16 (SAM), float32 (MoGe-3)", | |
| "steps": [ | |
| 25, | |
| 25 | |
| ], | |
| "input_size": [ | |
| 448, | |
| 672 | |
| ], | |
| "input": "id3_shutterstock_WildAnimal_Waterhole_2010559391/image.png and 0.png resized to 672x448", | |
| "formats": [ | |
| "gaussian", | |
| "gaussian_4", | |
| "mesh" | |
| ], | |
| "samples": [ | |
| { | |
| "seconds": 10.577361750009004, | |
| "peak_memory_gb": 9.539739473 | |
| }, | |
| { | |
| "seconds": 10.955263582989573, | |
| "peak_memory_gb": 9.578930137 | |
| }, | |
| { | |
| "seconds": 11.333075082977302, | |
| "peak_memory_gb": 9.518227537 | |
| } | |
| ], | |
| "median_seconds": 10.955263582989573, | |
| "peak_memory_gb": 9.578930137, | |
| "gaussians": 298112, | |
| "mesh_vertices": 330848, | |
| "mesh_faces": 655702, | |
| "pointmap_conditioned": true, | |
| "identical_latents_across_runs": true, | |
| "async_validation": { | |
| "request_ids": [ | |
| "0", | |
| "1" | |
| ], | |
| "event_loop_heartbeats": 3955, | |
| "latents_match_synchronous": true | |
| } | |
| } | |
| } | |