Publish Core AI artifact directories

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+*.mlirb filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,50 @@
+---
+library_name: coreai
+license: other
+tags:
+  - coreai
+  - ios
+  - macos
+  - on-device
+  - model-artifacts
+  - lenitas
+pipeline_tag: image-segmentation
+---
+
+# Lenitas Core AI Artifacts
+
+Hosted Core AI model artifacts for Lenitas.
+
+This repository contains already-exported Core AI directories that can be downloaded by the Lenitas iOS and macOS app. It does not contain model conversion code.
+
+Core AI assets keep the shape produced by `coreai-models`: either a standalone `.aimodel` directory or a resource bundle directory containing `metadata.json`, one or more `.aimodel` directories, tokenizers, schedulers, and related resources.
+
+## Contents
+
+```text
+index.json
+artifacts/
+  <model-id>/
+    <variant>/
+      metadata.json
+      *.aimodel/
+      tokenizer/
+```
+
+`index.json` is the app-facing download index. Each entry points to an artifact directory and includes platform support, minimum OS, total size, and per-file SHA-256 checksums.
+
+## Download
+
+The app reads:
+
+```text
+https://huggingface.co/lenitas/coreai-artifacts/resolve/main/index.json
+```
+
+For each selected artifact, the app downloads files under the entry's `path`, verifies each file, writes into a staging directory, and atomically moves the complete directory into Application Support.
+
+The installed directory is passed to the Core AI runtime or `coreai-models` Swift loader unchanged.
+
+## License
+
+Artifacts may have their own upstream licenses. See each `index.json` entry for license metadata when available.

artifacts/.gitkeep

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+

artifacts/efficientsam3-tinyvit/default/efficientsam3_tinyvit.aimodel/main.hash

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artifacts/efficientsam3-tinyvit/default/efficientsam3_tinyvit.aimodel/metadata.json

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+{
+  "assetVersion" : "2.0",
+  "producer" : "",
+  "creationDate" : "20260613T132523Z",
+  "description" : "EfficientSAM3 TinyViT (104M) text-prompt image segmentation. Distilled from SAM3. Source: github.com\/SimonZeng7108\/efficientsam3",
+  "license" : "",
+  "author" : ""
+}

artifacts/efficientsam3-tinyvit/default/metadata.json

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+{
+  "metadata_version": "0.2",
+  "kind": "segmenter",
+  "name": "efficientsam3_tinyvit",
+  "assets": {
+    "main": "efficientsam3_tinyvit.aimodel"
+  },
+  "user_data": {
+    "text_context_length": "16",
+    "text_pad_zero": "true",
+    "box_format": "cxcywh"
+  }
+}

artifacts/sam3/float16/metadata.json

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+{
+  "metadata_version": "0.2",
+  "kind": "segmenter",
+  "name": "sam3_float16",
+  "assets": {
+    "main": "sam3_float16.aimodel"
+  }
+}

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artifacts/sam3/float16/sam3_float16.aimodel/metadata.json

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+{
+  "description" : "SAM 3 is a unified foundation model for promptable segmentation in images and videos. It can detect, segment, and track objects using text or visual prompts such as points, boxes, and masks. This variant is explicitly for image segmentation. Source: https:\/\/github.com\/facebookresearch\/sam3",
+  "license" : "SAM License",
+  "assetVersion" : "2.0",
+  "creationDate" : "20260613T080026Z",
+  "author" : "N. Carion et al."
+}

artifacts/sam3/float16/tokenizer/tokenizer_config.json

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+{
+  "add_prefix_space": false,
+  "backend": "tokenizers",
+  "bos_token": "<|startoftext|>",
+  "clean_up_tokenization_spaces": false,
+  "do_lower_case": true,
+  "eos_token": "<|endoftext|>",
+  "errors": "replace",
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+  "max_length": 32,
+  "model_max_length": 32,
+  "pad_token": "<|endoftext|>",
+  "processor_class": "Sam3VideoProcessor",
+  "tokenizer_class": "CLIPTokenizer",
+  "unk_token": "<|endoftext|>"
+}

artifacts/sam3/w6palett-fp16/metadata.json

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+{
+  "metadata_version": "0.2",
+  "kind": "segmenter",
+  "name": "sam3_w6palett_fp16",
+  "assets": {
+    "main": "sam3_w6palett_fp16.aimodel"
+  }
+}

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artifacts/sam3/w6palett-fp16/sam3_w6palett_fp16.aimodel/metadata.json

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+{
+  "license" : "SAM License",
+  "description" : "SAM 3 image segmentation, 6-bit k-means palettized + fp16 residuals. Source: https:\/\/github.com\/facebookresearch\/sam3",
+  "assetVersion" : "2.0",
+  "author" : "N. Carion et al.",
+  "creationDate" : "20260613T102704Z"
+}

artifacts/sam3/w6palett-fp16/tokenizer/tokenizer_config.json

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+{
+  "add_prefix_space": false,
+  "backend": "tokenizers",
+  "bos_token": "<|startoftext|>",
+  "clean_up_tokenization_spaces": false,
+  "do_lower_case": true,
+  "eos_token": "<|endoftext|>",
+  "errors": "replace",
+  "is_local": false,
+  "local_files_only": true,
+  "max_length": 32,
+  "model_max_length": 32,
+  "pad_token": "<|endoftext|>",
+  "processor_class": "Sam3VideoProcessor",
+  "tokenizer_class": "CLIPTokenizer",
+  "unk_token": "<|endoftext|>"
+}

index.json

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+{
+  "version": 1,
+  "host": "huggingface",
+  "repo": "lenitas/coreai-artifacts",
+  "models": [
+    {
+      "id": "efficientsam3-tinyvit",
+      "variant": "default",
+      "platforms": [
+        "iOS",
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+  "revision": "main"
+}