quantized duplicated precisions.json, which is authoritative for the
quantized/non-quantized partition. default expressed a per-repository
recommendation nothing consumed: the library resolves its own per-platform
default. Both are gone from the schema.
The previous removal commit said earlier tags still contain the MLX artifacts. That is wrong: MLX for this model was only ever published on main / v0.10.0, and no tag at v0.9.0 or below ever carried it. The files remain recoverable from git history. v0.9.0 and below are, and have been, untouched.
Remove MLX artifacts: 7.5-19.6x slower than Core ML on device
MLX measured substantially slower than Core ML on an iPhone 16 for every convolutional vision model tested (efficientnet-v2-s 19.6x, yolo26-s 16.0x, yolo26-seg-s 7.5x, yolo26-pose-n 10.0x). MLX weight quantization also cannot shrink a conv model, since it only rewrites nn.Linear/embedding modules.
The .pte and config.json are removed; each mlx/ dir keeps a NOTES.md with the measurements. The exporter is retained in export-scripts so this can be re-tested against a future ExecuTorch/MLX release.
Earlier tags (v0.9.0 and below) are untouched and still contain the MLX artifacts.
