| --- |
| license: apache-2.0 |
| library_name: coreml |
| tags: |
| - core-ml |
| - siglip |
| - sentence-transformers |
| - embeddings |
| - on-device |
| base_model: |
| - google/siglip-base-patch16-384 |
| - sentence-transformers/all-MiniLM-L6-v2 |
| --- |
| |
| # gallerywise/coreml-embeddings |
|
|
| Core ML (`.mlpackage`, fp16, `cpu_and_gpu`) conversions of the embedding backbones |
| used by the on-device pipeline in **gallerywise.ai**. Converted with |
| [`scripts/coreml/convert_embeddings.py`](https://github.com/ADR-007/aibom-macos) |
| (AIB-72 / AIB-119); loaded at runtime through pyobjc Core ML with **no torch** in |
| the shipped app. |
|
|
| ## Contents |
|
|
| | File | Source model | Notes | |
| |------|--------------|-------| |
| | `siglip_vision.mlpackage.zip` | `google/siglip-base-patch16-384` | vision tower, 768-D | |
| | `siglip_text.mlpackage.zip` | `google/siglip-base-patch16-384` | text tower, 768-D | |
| | `text_embed.mlpackage.zip` | `sentence-transformers/all-MiniLM-L6-v2` | 384-D; mean-pool + L2-normalize baked into the graph (fixed seq-len 64) | |
| | `siglip_logit_params.json` | — | SigLIP logit scale/bias | |
|
|
| The `.mlpackage` bundles are directories, so they are hosted **zipped** (each |
| archive contains exactly one top-level `*.mlpackage/` entry). The client fetches, |
| sha256-verifies, and unzips them on first launch. |
|
|
| ## License & attribution |
|
|
| Apache-2.0, inherited from both source models |
| ([SigLIP](https://huggingface.co/google/siglip-base-patch16-384), |
| [all-MiniLM-L6-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2)), |
| which are themselves Apache-2.0. These are format conversions (Core ML) of those |
| weights — no retraining or fine-tuning. |
|
|
| ## Intended use |
|
|
| The gallerywise.ai macOS app's embedding stages (semantic search, zero-shot tags, |
| near-duplicate / moment grouping). Not a general-purpose endpoint. |
|
|
