Instructions to use verdict-models/laya-multilingual with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Laya
How to use verdict-models/laya-multilingual with Laya:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
Laya Multilingual (Verdict-ready)
The Laya Multilingual System One decision model (mmBERT-base, 100+ languages), exported to ONNX fp32 and packaged for Verdict -- a high-performance serving engine for System One decision models. Serve it with one command:
# CPU host
docker run --rm -p 8080:8080 \
-v ~/.cache/verdict:/root/.cache/verdict \
sgyaqing/verdict:latest-cpu serve verdict-models/laya-multilingual --host 0.0.0.0
# GPU host
docker run --rm --gpus all -p 8080:8080 \
-v ~/.cache/verdict:/root/.cache/verdict \
sgyaqing/verdict:latest-cuda serve verdict-models/laya-multilingual --host 0.0.0.0
# ModelScope:
docker run --rm -p 8080:8080 \
-e VERDICT_USE_MODELSCOPE=1 \
-v ~/.cache/verdict:/root/.cache/verdict \
sgyaqing/verdict:latest-cpu serve sgyaqing/laya-multilingual --host 0.0.0.0
For English-only workloads, use verdict-models/laya.
Endpoints: the standard decision protocols POST /v1/systemone and POST /v1/decisions, native POST /v1/choice | /v1/score | /v1/noul, plus an OpenAI-compatible layer (/v1/chat/completions, /v1/models).
Performance
Measured on one RTX 4090, end to end over HTTP, against the model author's own server (laya-serve). A ratio above 1x means Verdict is ahead.
| concurrency | Verdict rps | laya-serve rps |
rps ratio | Verdict P50 / P99 (ms) | laya-serve P50 / P99 (ms) |
P50 / P99 ratio |
|---|---|---|---|---|---|---|
| 1 | 123.2 | 49.1 | 2.51x | 8.03 / 10.29 | 18.54 / 28.92 | 2.31 / 2.81x |
| 8 | 553.4 | 46.3 | 11.9x | 13.99 / 19.79 | 184.36 / 204.24 | 13.2 / 10.3x |
| 64 | 2534.4 | refused requests | โ | 24.67 / 32.23 | refused requests | โ |
Files
| File | Purpose |
|---|---|
model.json |
manifest: graph file name, budgets, calibration, special-token names |
laya-multilingual.onnx |
the ONNX graph (fp32) |
tokenizer/tokenizer.json (+ tokenizer_config.json) |
the tokenizer |
SHA256SUMS |
checksums for every file above |
Provenance & fidelity
Weights are unchanged from convaiinnovations/laya-multilingual; this repo adds only the ONNX export and the serving manifest. Conversion and serving are verified against the golden standard (the official Laya SDK, CPU fp32, 43-case corpus): identical answers on CPU; on CUDA (RTX 4090) within 1e-4.
Accuracy PK โ against laya-serve 0.4.7; both servers on one RTX 4090 (CUDA), graded against the same golden standard:
| Verdict | laya-serve |
result | |
|---|---|---|---|
| worst deviation | 1e-4 | 1.74 | Verdict ahead |
License
Apache-2.0, inherited from the base model. Credit for the model itself belongs to the original authors; this repository only repackages it for serving.
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Base model
convaiinnovations/laya-multilingual