jina-omni-webgpu / README.md
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---
title: Jina v5 Omni WebGPU
emoji: "\U0001F3B5"
colorFrom: indigo
colorTo: blue
sdk: static
pinned: false
license: cc-by-nc-4.0
short_description: Cross-modal search on WebGPU with jina-embeddings-v5-omni
models:
- jinaai/jina-embeddings-v5-omni-nano
- onnx-community/jina-embeddings-v5-omni-nano-ONNX
tags:
- multimodal
- cross-modal-retrieval
- webgpu
- transformers.js
- onnx
- jina-embeddings
---
# jina · omni · webgpu
In-browser cross-modal search powered by [`jinaai/jina-embeddings-v5-omni-nano`](https://huggingface.co/jinaai/jina-embeddings-v5-omni-nano) running entirely on WebGPU via [transformers.js](https://huggingface.co/docs/transformers.js) v4 + ONNX Runtime Web.
One vector space for **text, images, audio, and (eventually) video** — a text query ranks image/audio corpus items and vice-versa without re-indexing.
## What's inside
- **Model load gate** with a precision selector (`q4f16` default — 2.14 GB, or `fp16` for cleaner numerics at 2.68 GB). All three task-specific ONNX graphs (text / vision / audio) download in parallel with per-bundle progress bars; cached in your browser for subsequent loads.
- **Curated query chips** to demo cross-modal retrieval against the seeded corpus.
- **Result cards** render the actual asset — image thumbnails inline, audio with a ▶/❚❚ inline play toggle. When audio rarely cracks top-K (v5-omni's text→audio alignment is weaker than text→image), the closest audio match is appended after the top-K with an explainer.
- **Corpus editor** — clear the seeded 25-item corpus and add your own text / image / audio. Embedding runs in-browser via the same ONNX session the query uses.
## Assets + attribution
The seeded corpus mixes 12 text snippets, 10 instrument photos, and 3 audio clips — all images and audio are sourced from [Wikimedia Commons](https://commons.wikimedia.org/) with full inline artist + license + source attribution. Model license is **CC BY-NC 4.0** (inherited from the base model — non-commercial use only; contact `sales@jina.ai` for commercial).
## Links
- Base model: [jinaai/jina-embeddings-v5-omni-nano](https://huggingface.co/jinaai/jina-embeddings-v5-omni-nano)
- Blog: [Jina embeddings v5 omni](https://jina.ai/news/jina-embeddings-v5-omni-multimodal-embeddings-for-text-image-audio-and-video/)
- ONNX weights: [onnx-community/jina-embeddings-v5-omni-nano-ONNX](https://huggingface.co/onnx-community/jina-embeddings-v5-omni-nano-ONNX)