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appautomaton/sam3.1-multiplex-bf16-mlx
sam3.1-multiplex-bf16-mlx is a mask generation model from appautomaton. Use it for the mask generation task on the model card, and read the license before you ship it in a product. It is set up for mlx. The card lists the license as other.
Final-layout BF16 detector and Object Multiplex tracker weights for running Meta SAM 3.1 with mlx-cv on Apple Silicon. BF16 is reduced precision, not integer quantization.
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From the Hugging Face model README
Final-layout BF16 detector and Object Multiplex tracker weights for running Meta SAM 3.1 with mlx-cv on Apple Silicon. BF16 is reduced precision, not integer quantization.
pip install "mlx-cv[mlx,hub]"
from mlx_cv.models.sam3 import SAM3Processor, SAM3VideoSession
image_model = SAM3Processor.from_pretrained("sam3.1")
prediction = image_model.predict(image, "person")
video = SAM3VideoSession.from_pretrained("sam3.1")
The strict 1963-tensor BF16 checkpoint loads directly into MLX with no runtime PyTorch conversion. The persisted Metal image gate reached mask IoU 0.999618, maximum box error 0.1626 px, and score error 0.001305 against the official reference. The multiplex decoder mask IoU was 0.99215, with official MPS component checks and real two-frame MLX propagation also passing.
Meta's source Hugging Face repository requires users to accept access terms. This derivative MLX checkpoint is distributed publicly by App Automaton under the bundled SAM License; downloading or using it constitutes acceptance of those terms. Review the complete LICENSE before use.