Publish Core ML FP32 artifact

README.md

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+---
+license: mit
+library_name: coreml
+base_model: ZhengPeng7/BiRefNet_lite
+tags:
+- coreml
+- apple
+---
+
+# BiRefNet Lite 1024 for Core ML
+
+Unofficial Core ML conversion and Apple-platform validation record for the
+pinned upstream checkpoint. Source and reproducibility tooling are in
+[miracle2k/birefnet-lite-coreml](https://github.com/miracle2k/birefnet-lite-coreml).
+
+| Artifact | Apple target | Status |
+| --- | --- | --- |
+| `fp32/r1` | iOS 17+ | Stable; CPU-only execution is recommended |
+
+Each artifact directory contains exactly one `.mlpackage.zip`, `manifest.json`,
+and `SHA256SUMS`. Verify a downloaded directory with:
+
+    shasum -a 256 -c SHA256SUMS
+
+Pin the exact artifact path and archive SHA. P8 is retained in the source
+repository as experiment evidence only; no P8 package is published here.

artifacts.json

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+{
+  "schema_version": 1,
+  "artifacts": [
+    {
+      "path": "fp32/r1",
+      "status": "stable",
+      "minimum_deployment_target": "iOS17",
+      "archive": "BiRefNetLite-1024-FP32-iOS17-r1.mlpackage.zip",
+      "sha256": "c6fa3bcedc42f304c754cfc597e9c72f097fa0e3b16866166fbd76e4f2d6e11d"
+    }
+  ]
+}

fp32/r1/BiRefNetLite-1024-FP32-iOS17-r1.mlpackage.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:c6fa3bcedc42f304c754cfc597e9c72f097fa0e3b16866166fbd76e4f2d6e11d
+size 164852428

fp32/r1/SHA256SUMS

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+c6fa3bcedc42f304c754cfc597e9c72f097fa0e3b16866166fbd76e4f2d6e11d  BiRefNetLite-1024-FP32-iOS17-r1.mlpackage.zip
+69b75fc8f86142912a18768711cde2cd37ace6608c63da5f11afebb35772bf05  manifest.json

fp32/r1/manifest.json

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+{
+  "archive": {
+    "bytes": 164852428,
+    "filename": "BiRefNetLite-1024-FP32-iOS17-r1.mlpackage.zip",
+    "sha256": "c6fa3bcedc42f304c754cfc597e9c72f097fa0e3b16866166fbd76e4f2d6e11d"
+  },
+  "artifact": {
+    "id": "fp32-r1",
+    "recommended": true,
+    "revision": "r1",
+    "status": "stable",
+    "variant": "fp32"
+  },
+  "base_model": {
+    "license": "MIT",
+    "repository": "ZhengPeng7/BiRefNet_lite",
+    "revision": "7838f1c3472f827cd8ce13ab5ccc2ce48077360f",
+    "source_files_sha256": {
+      "BiRefNet_config.py": "e7b8c2a74f6cea6a59553d517f71d47f2c1d90e670a13416af17c25fe2f3dc52",
+      "birefnet.py": "af8568b5be406bf4d2a68a7ed6d72e40f73b37a1fb6fc9ebd71b5b3cbcd069c9",
+      "config.json": "9dc8614fccddd40c601aeadc69b9db6dd820598179b2a2198492e6ffa016a824",
+      "model.safetensors": "4417d89795250e698c3cb0ae8df15743810065f646f48a694fdfa7ca052d0815"
+    }
+  },
+  "contract": {
+    "external_preprocessing": {
+      "id": "rgb01-imagenet-normalized-nchw-v1",
+      "steps": [
+        "resize or letterbox the oriented RGB source to 1024x1024",
+        "scale RGB channel values to [0, 1]",
+        "normalize each channel with the listed ImageNet mean and standard deviation",
+        "arrange as Float32 NCHW with shape [1, 3, 1024, 1024]"
+      ]
+    },
+    "input": {
+      "dtype": "float32",
+      "imagenet_mean": [
+        0.485,
+        0.456,
+        0.406
+      ],
+      "imagenet_standard_deviation": [
+        0.229,
+        0.224,
+        0.225
+      ],
+      "layout": "NCHW",
+      "name": "image",
+      "shape": [
+        1,
+        3,
+        1024,
+        1024
+      ],
+      "type": "MLMultiArray"
+    },
+    "output": {
+      "activation": "logits; apply sigmoid for foreground probabilities",
+      "dtype": "float32",
+      "name": "mask_logits",
+      "shape": [
+        1,
+        1,
+        1024,
+        1024
+      ]
+    }
+  },
+  "license": "MIT",
+  "license_files_in_archive": [
+    "LICENSE",
+    "LICENSE-BIREFNET",
+    "LICENSE-COREML-BIREFNET",
+    "NOTICE"
+  ],
+  "package": {
+    "bytes": 187127482,
+    "filename": "BiRefNetLite-1024-FP32.mlpackage",
+    "minimum_deployment_target": "iOS17",
+    "model_graph_sha256": "8361b88d3983009225c4cbcea006c7d7db7b3bfc7778a2c832a5f9ff0caf22b7",
+    "precision": "fp32",
+    "quantization": "none",
+    "recommended_compute_units": "CPU_ONLY",
+    "source_tree_sha256": "1622f2b216b41bfa3f764057aa7f37054b193666191e8f4b17497e587fff1ec9",
+    "tree_sha256": "a93f903c25bf34794a04ce3fc7a13676a9cff0ad0cc1ab0a67314f4271335d6b",
+    "weights_sha256": "43c6ae668bfe95bccac0806e6b0b05456112ea635c84ec5a6f8519f6af07f74a"
+  },
+  "provenance": {
+    "conversion_source_commit": "6aafb3cae82dfa4660e485aab37a8187fdcd38f7",
+    "conversion_source_repository": "https://github.com/miracle2k/birefnet-lite-coreml",
+    "coremltools": "9.0",
+    "format": "mlprogram",
+    "python": ">=3.12,<3.13",
+    "torch": "2.5.1"
+  },
+  "schema_version": 1
+}