Instructions to use verdict-models/laya with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Laya
How to use verdict-models/laya 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 (Verdict-ready)
The Laya System One decision model, 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 --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 --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 --host 0.0.0.0
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 | 121.4 | 34.4 | 3.53x | 8.37 / 11.07 | 28.58 / 32.73 | 3.42 / 2.96x |
| 8 | 501.4 | 35.4 | 14.2x | 15.99 / 22.42 | 227.96 / 250.60 | 14.3 / 11.2x |
| 64 | 1353.0 | refused requests | โ | 46.71 / 65.19 | refused requests | โ |
Files
| File | Purpose |
|---|---|
model.json |
manifest: graph file name, budgets, calibration temperatures |
laya.onnx + laya.onnx.data |
the ONNX graph (fp32, external weights) |
tokenizer/tokenizer.json (+ tokenizer_config.json) |
the tokenizer |
SHA256SUMS |
checksums for every file above |
Provenance & fidelity
Weights are unchanged from convaiinnovations/laya; 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, 40-case corpus): identical answers on CPU and on CUDA (RTX 4090).
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 | 0.0 | 0.943 | 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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Model tree for verdict-models/laya
Base model
convaiinnovations/laya