fp16 MLX conversion of ZhengPeng7/BiRefNet (Swin-L, 1024) — soft-alpha matting

README.md

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+---
+license: mit
+base_model: ZhengPeng7/BiRefNet
+library_name: mlx
+tags:
+  - mlx
+  - image-segmentation
+  - matting
+  - background-removal
+  - birefnet
+pipeline_tag: image-segmentation
+---
+
+# BiRefNet-fp16 (MLX)
+
+[`mlx-community/BiRefNet-fp16`](https://huggingface.co/mlx-community/BiRefNet-fp16) is an **fp16 MLX** conversion
+of [`ZhengPeng7/BiRefNet`](https://huggingface.co/ZhengPeng7/BiRefNet) (MIT) — a Swin-L + ASPP-Deformable
+foreground segmentation / matting model at **1024×1024**, producing a single-channel soft-alpha matte
+(white = foreground). The fast, general-purpose tier.
+
+**Parity:** IoU **0.9905** vs the PyTorch reference (zero unused keys). fp16 runtime validated for production
+matting quality.
+
+## Use (Swift / MLX)
+
+Loaded by [`mlx-birefnet-swift`](https://github.com/xocialize/mlx-birefnet-swift) — the vendored `BiRefNet`
+core plus a conformant MLXEngine `matting` ModelPackage:
+
+```swift
+import BiRefNet
+let pipeline = try BiRefNetPipeline.fromPretrained("model.safetensors", dtype: .float16)  // inputSize 1024
+let matte = try pipeline(cgImage).maskCGImage()   // source-resolution soft-alpha
+```
+
+Converted from the official PyTorch checkpoint via the package's `birefnet-convert` (PyTorch NCHW → MLX NHWC;
+754 → 687 tensors). Single-file `model.safetensors`. See also the higher-res tier
+[`mlx-community/BiRefNet_HR-matting-fp16`](https://huggingface.co/mlx-community/BiRefNet_HR-matting-fp16).

model.safetensors

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+size 440483842