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Download README.md from elcodabra/seklu-e5-small-coreml: direct link, hf CLI and curl.
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https://huggingface.co/elcodabra/seklu-e5-small-coreml/resolve/main/README.md
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metadata
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 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-256ac5a88751994cce0844a96af3ff79bdb8dec100c3439057b176172a760f4c41a), holding:E5Small.mlmodelc: compiled Core ML model; inputsinput_ids,attention_mask(int32, 1×16/32/64/128/256), outputembedding(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:orpassage:as the original model card says. - Checked against PyTorch: cosine ≥ 0.9998 on EN/RU texts; a Swift tokenizer from
vocab.tsvgave the same ids as Hugging Facetokenizerson 1511 of 1511 test strings.
License: MIT, as the original model (see LICENSE).