paraphrase-multilingual-MiniLM-L12-v2 embeddings (384-d, 50+ languages)

models.skillsafe.ai/paraphrase-multilingual-minilm-l12-v2@e8f8c211/

Vetted New WebGPU

Feature extraction model for transformers.js (fp32). Runs on WASM or WebGPU — 449 MB downloaded once from models.skillsafe.ai, then cached for every SkillSafe app that uses it. Inference happens on your device; nothing you enter is uploaded to load it, and it never costs a credit. Weights from Hugging Face · skillsafe-ai/paraphrase-multilingual-minilm-l12-v2, pinned at c5f1118905ef — also loadable straight from Hugging Face outside SkillSafe (how).

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Details

Catalogue idparaphrase-multilingual-minilm-l12-v2@e8f8c211
Runtimetransformers.js ≥ 3.0.0
DeviceWASM, WebGPU
Variantfp32
Download449 MB · 1 file
LicenceApache-2.0 · notice
Pinned atc5f1118905efa99ffaaa4881148379a6688806f1
ApprovedSep 22, 2026
Statusactive — every file is a live vetted hash

Files

Each file is served at an immutable URL; the canonical form is the SHA-256 itself. Tokenizer and config JSON are not here by design — they ship in your app bundle.

PathFormatSizeSHA-256
onnx/model.onnx onnx 449 MB 10f7a0884202…55a05a

Signature

Graph inputs and outputs read from the ONNX bytes at vetting — the tensor names your session.run() call feeds and reads. Symbolic dimensions are shown by name.

Inputs

  • input_ids int64 [batch_size, sequence_length]
  • attention_mask int64 [batch_size, sequence_length]
  • token_type_ids int64 [batch_size, sequence_length]

Outputs

  • last_hidden_state float32 [batch_size, sequence_length, 384]
Use it in an app declaration · SDK loader · transformers.js · URLs · Hugging Face — generated from this entry

Add to the body of POST /v1/apps/{slug}/releases (or a release session). An unknown or withdrawn model is refused with a 400 naming it; the app page then shows "downloads 449 MB · runs on your device" and /models.txt carries the attribution.

{
  "models": [
    {
      "id": "paraphrase-multilingual-minilm-l12-v2",
      "revision": "e8f8c211"
    }
  ]
}

Evaluation

onnx.checker + onnxruntime CPU smoke run with zero-filled inputs at the declared shapes; per-file SHA-256 pinned to the source; ONNX output vs the PyTorch model from the same commit on real text (import.parity) — imported as published upstream, then checked. Evaluated Sep 22, 2026.

Parity against transformers BertModel from same snapshot, fp32 · last_hidden_state

fileprecisionmax absmean abscosine / PSNR
onnx/model.onnxfp322.1e-62.3e-71.000000

Runs under onnxruntime

Zero-filled inputs at the declared shapes, CPU execution provider on the converter host; the check is that the graph loads, runs, and emits the declared output shapes.

  • onnx/model.onnx: input_ids[1,8], attention_mask[1,8], token_type_ids[1,8] → last_hidden_state[1,8,384] 2 ms

Toolchain: python 3.12.13 · platform Darwin 25.6.0 arm64 · torch 2.10.0 · onnx 1.23.0 · onnxruntime 1.30.0. Recipe models/recipes/paraphrase-multilingual-minilm-l12-v2.yaml (bff3a6d0ae49). Full manifest.json

Licence & attribution

Apache-2.0 · licence text · notice

paraphrase-multilingual-MiniLM-L12-v2: sentence-transformers (Nils Reimers et al.), Apache License 2.0. https://huggingface.co/sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2 — the repo's own ONNX export.

Apps that declare this model get this text in their generated /models.txt, so a licence that requires a notice always carries one.

Every file here was approved by exact SHA-256 after a structural audit of the graph, fetched from a content-pinned source, and is served credential-free at an immutable URL. The SDK re-verifies the hash on your device before it caches or returns anything. Missing a variant? Request it — or read how the registry works.