README.md

metadata

license: other
license_name: mixed-permissive
license_link: https://huggingface.co/umbml/arca-models/blob/main/LICENSES.md
library_name: onnx
tags:
  - onnx
  - coreml
  - clip
  - face-recognition
  - mirror

arca-models

Pinned ONNX mirrors of third-party models used for on-device inference in Arca. Nothing here is trained by us — every file is a byte-for-byte copy of an upstream release, re-hosted so that:

1. Downloads are immutable. Arca pins each file by commit SHA and verifies a SHA-256 before use. Fetching upstream main gave us a moving target: two of our source URLs 404'd after upstream repos were restructured, silently breaking on-device features with nothing able to detect the drift.
2. Upstream repos aren't used as a CDN. Pulling a 261 MB file from a github.com/.../raw/main/ URL on every client install is not what that endpoint is for.

If you want these models, please prefer the original sources below — they are the authoritative, maintained copies.

Contents

Every file here is live in Arca. Nothing is staged "for later" — an unused model in a mirror is just a file nobody can explain a year from now.

File	Bytes	Upstream source	License
arcface.onnx	261,036,388	onnx/models — arcfaceresnet100-8.onnx	Apache-2.0
auraface.mlpackage.zip	241,915,367	fal/AuraFace-v1 — glintr100.onnx, converted to Core ML	Apache-2.0
clip-vit-b32-image.onnx	351,686,194	Qdrant/clip-ViT-B-32-vision	MIT
clip-vit-b32-text.onnx	254,102,519	Qdrant/clip-ViT-B-32-text	MIT
bpe_simple_vocab_16e6.txt.gz	1,356,917	openai/CLIP	MIT

SHA-256

f3a6bc281e72f88862f5748b53be3d76b3b48f8f1ab1f4a537941bdc4e1b01da  arcface.onnx
7c47e081da5a8eb50c7f34faea9cbffa3f4f95a7e08c0c359ad3a4fa7610aaee  auraface.mlpackage.zip
c68d3d9a200ddd2a8c8a5510b576d4c94d1ae383bf8b36dd8c084f94e1fb4d63  clip-vit-b32-image.onnx
4dbe762b11e36488304471e439cde89da053ad7acaddbf9e096745d142ec8d8b  clip-vit-b32-text.onnx
924691ac288e54409236115652ad4aa250f48203de50a9e4722a6ecd48d6804a  bpe_simple_vocab_16e6.txt.gz

Note on auraface.mlpackage.zip

A .mlpackage is a directory bundle, not a single file, so it is zipped (ditto -c -k --sequesterRsrc --keepParent) for single-URL distribution and single-SHA-256 pinning, matching every other file in this repo. The installing client (FaceModelInstaller.swift) unzips it before handing it to MLModel.compileModel(at:) — it never compiles the zip directly.

Converted from glintr100.onnx (from the same fal/AuraFace-v1 repo as its sibling scrfd_10g_bnkps.onnx/2d106det.onnx/1k3d68.onnx/genderage.onnx — only glintr100.onnx is mirrored here. The rest of that repo is stock InsightFace detection/auxiliary models with non-commercial upstream terms; glintr100.onnx is the one file fal/AuraFace-v1's own LICENSE.md (stock Apache-2.0, verified in full, no field-of-use rider) actually covers, and it is the only one Arca needs — detection and landmarks come from the OS's own face API on every platform, never from this mirror. Bridge: ONNX → PyTorch via onnx2torch (coremltools dropped direct ONNX conversion) → traced → coremltools.convert(..., convert_to="mlprogram"). Verified against the original ONNX output on 5 real photos: max abs diff ~5e-6, cosine similarity 1.0 — floating-point noise, not a converter defect.

Note on the CLIP pair

clip-vit-b32-image.onnx and clip-vit-b32-text.onnx come from the same export family (both PyTorch 2.3.0 exports of clip-ViT-B-32) and therefore share one 512-d embedding space. Mixing an image encoder from one port with a text encoder from another puts the vectors in different spaces and makes cosine similarity meaningless. Treat the two as a single atomic unit.

Previously here, removed

Both were removed from main by a normal commit, so earlier pinned resolve/<sha>/ URLs still resolve — nothing that referenced them breaks.

• yunet.onnx (face detection, MIT) — Arca uses the OS Windows.Media.FaceAnalysis.FaceDetector for detection, so this was never loaded. arcface.onnx (the 512-d embedder) is the only ONNX face model.
• yolox_tiny.onnx (object detection, Apache-2.0) — mirrored in anticipation of an object-detection feature that doesn't exist yet, then removed rather than left sitting here unused. If it comes back, it will be re-uploaded alongside the code that actually calls it.

Licensing

Each file keeps its upstream license; see the table above and LICENSES.md. The license: other / mixed-permissive marker reflects that this repo aggregates MIT and Apache-2.0 files rather than being under one single license. No copyleft-licensed weights are hosted here — see LICENSES.md for why Ultralytics YOLO in particular can never be.