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markdownnn/recall-granite-q8
recall-granite-q8 is a feature extraction model from markdownnn. Use it when you need embeddings to search or compare text. It is set up for transformers.js. The card lists the license as apache-2.0.
INT8-quantized ONNX build of ibm-granite/granite-embedding-107m-multilingual, prepared for fully on-device semantic search in Recall — a privacy-first Chrome extension that re-finds the pages you've read, entirely in…
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.onnx107 MB · 86%
From the Hugging Face model README
INT8-quantized ONNX build of
ibm-granite/granite-embedding-107m-multilingual,
prepared for fully on-device semantic search in
Recall — a privacy-first Chrome extension that
re-finds the pages you've read, entirely in your browser (zero network egress).
ibm-granite/granite-embedding-107m-multilingual (Apache-2.0)optimum — 384-dim embeddingstransformers.js + onnxruntime-web
(WebGPU, with a WASM fallback). No server, no data leaves the device.onnx/model_quantized.onnx, tokenizer.json, config.json, tokenizer_config.jsonThe Recall extension downloads these files once (or builds them via the included
scripts/quantize-granite.py recipe) and bundles them; all capture, embedding, and search
then happen on-device.
Reproduced from IBM's official fp32 release → ONNX export → optimum AVX2 dynamic INT8.
See scripts/quantize-granite.py in the Recall repo.
Apache-2.0, inherited from the base model. This is a quantized derivative; all credit for the underlying model goes to IBM Granite. See the base model card for full terms.