elcodabra/seklu-e5-small-coreml

multilingual-e5-small, Core ML (int8)

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).