README.md

---
license: apache-2.0
base_model: convaiinnovations/laya
library_name: onnx
tags:
  - laya
  - system-one
  - typed-decisions
  - onnx
  - webgpu
  - transformers.js-free
pipeline_tag: text-classification
---

# laya-multilingual · split ONNX for the browser (WebGPU → WASM)

An **unmodified** ONNX export of the `multilingual` checkpoint of
[`convaiinnovations/laya`](https://huggingface.co/convaiinnovations/laya) (mmBERT-base encoder + decision head,
322M params, 100+ languages), in the split format that [`laya-ts`](https://github.com/NandhaKishorM/laya/tree/main/laya-ts)
loads with ONNX Runtime Web:

| file | size | runs on |
|---|---|---|
| `encoder.onnx` + `encoder.onnx.data` | 1.23 GB (fp32) | WebGPU, falls back to WASM |
| `head.onnx` + `head.onnx.data` | 60 MB | WASM |
| `tokenizer.json`, `rl_agent_config.json` | 34 MB | — |

Exported at laya commit `6d942c92081fbc139e736bbd9ac0023223c29b7f` with

```bash
python laya-ts/scripts/export_onnx.py --repo convaiinnovations/laya --subfolder multilingual --out-dir ./model-ml
```

which checks torch vs ONNX outputs agree within 1e-4 (measured max diff 2.9e-6).

## Use it

```js
import { Agent } from "laya-ts";
const agent = await Agent.load("https://huggingface.co/Steven10429/laya-multilingual-webgpu/resolve/main/");
const r = await agent.predict("我打开设置页面应用就闪退。", {
  department: { type: "choice", instructions: "Which department should handle this?",
                criteria: { billing: "invoices, payments, refunds", technical: "bugs, crashes", other: "everything else" } },
});
```

Measured in Chrome on an Apple M4 Pro (3 questions, 163 input tokens): **WebGPU p50 ≈ 148 ms**, forced WASM p50 ≈ 808 ms,
identical answers. Works inside a cross-site iframe (e.g. an itch.io embed) — Hugging Face serves these files with CORS.

## Caveats (from upstream)

The base checkpoints are close to chance zero-shot on the typed-decisions benchmark; fine-tune on your own decisions for
real accuracy. Probabilities are not interchangeable with other System One models — recalibrate thresholds.

## License & attribution

Apache-2.0, same as the original weights by ConvAI Innovations / Nandakishor M
([NandhaKishorM/laya](https://github.com/NandhaKishorM/laya)). This repository only changes the file format.