license: apache-2.0
base_model: Qwen/Qwen3-Embedding-0.6B
tags:
- text-embeddings
- sentence-similarity
- retrieval
- core-ai
- apple-silicon
- macos
library_name: swift-text-embedder
embed-qwen3 — Qwen3-Embedding-0.6B for Core AI (macOS 27)
Alibaba's Qwen3-Embedding-0.6B (Apache 2.0)
exported to an Apple Core AI .aimodel for on-device text embeddings and semantic search. Read by
swift-text-embedder and the
embed command-line tool.
Files
| Path | What |
|---|---|
embed-qwen3-0.6b-float32.aimodel/ |
Entry points t128 and t512: token ids [1, L] + attention mask [1, L] (int32, LEFT-padded with `< |
embed-support/vocab.json, merges.txt |
The checkpoint's own Qwen2 byte-level BPE files. |
embed-support/config.json |
The pad / end-of-text id, the exported lengths, the dimension. |
The host tokenises (NFC, Qwen2's pre-tokeniser, end-of-text appended), pads on the left, picks the
shortest length that holds the text, and L2-normalises the output. Queries are embedded as
Instruct: <task>\nQuery: <text>, documents as they are, per the model card.
Fidelity
Against transformers 5.17 on the same inputs: tokenizer ids and masks identical over 13 texts at
both lengths (Unicode, code, newlines included); embeddings 125–126 dB PSNR, cosine ≥ 0.999999.
The fixed-length left padding changes an embedding by at most 3e-7 against the unpadded model.
Use
hf download arraypress/embed-qwen3 --local-dir models
embed model install models
embed index ~/Notes && embed search "how do I rotate the API key"
Requires macOS 27 (Core AI) on Apple silicon. Converted with coreai-torch 0.4.2 / torch 2.13.