| --- |
| license: mit |
| base_model: intfloat/multilingual-e5-small |
| library_name: coreml |
| pipeline_tag: sentence-similarity |
| language: [en, ru, es] |
| tags: [coreml, sentence-embeddings, e5, macos] |
| --- |
| |
| # multilingual-e5-small, Core ML (int8) |
|
|
| [intfloat/multilingual-e5-small](https://huggingface.co/intfloat/multilingual-e5-small) converted to Core ML for |
| local file search on macOS (Seklu). Nothing else changed: same weights (int8-quantized), same tokenizer. |
|
|
| - `e5-small-coreml-v1.zip` (112,357,732 bytes, |
| SHA-256 `ac5a88751994cce0844a96af3ff79bdb8dec100c3439057b176172a760f4c41a`), holding: |
| - `E5Small.mlmodelc`: compiled Core ML model; inputs `input_ids`, `attention_mask` (int32, 1×16/32/64/128/256), |
| output `embedding` (384, mean-pooled and L2-normalised inside the model). macOS 15+. |
| - `vocab.tsv`: the SentencePiece Unigram vocabulary (piece TAB score, line number = id). |
| - Prefix texts with `query: ` or `passage: ` as the original model card says. |
| - Checked against PyTorch: cosine ≥ 0.9998 on EN/RU texts; a Swift tokenizer from `vocab.tsv` gave the same ids |
| as Hugging Face `tokenizers` on 1511 of 1511 test strings. |
| |
| License: MIT, as the original model (see `LICENSE`). |
|
|
