metadata
license: apache-2.0
task_categories:
- text-classification
language:
- en
tags:
- decision-model
- calibration
- onnx
- laya
pretty_name: laya-onnx decision eval
laya-onnx decision eval
A small, reproducible self-check for laya-onnx —
an ONNX Runtime backend for Laya typed System-1 decisions (choice / score /
noul, no generated tokens).
Files
| file | what |
|---|---|
decisions.jsonl |
8 labeled states / 10 questions with gold answers |
results.json |
raw published results (accuracy, MAE, ECE, latency) |
results.md |
method + published numbers |
checksums.json |
SHA-256 manifest of the receptron/laya-onnx bundle |
Published result
CPU run (Windows 11, Intel i7-1255U, onnxruntime), bundle receptron/laya-onnx
@ 68f27dfe:
| question type | n | accuracy | MAE | ECE |
|---|---|---|---|---|
| choice | 4 | 1.00 | – | 0.456 |
| noul | 4 | 1.00 | – | 0.129 |
| score | 2 | 0.50 | 0.530 | 0.112 |
| overall | 10 | 0.90 | – | 0.256 |
Latency per predict() call: mean 2808 ms / p50 1760 ms / p95 7418 ms.
This is a reproducibility self-check, not a leaderboard — the sample is tiny and the intervals are wide.
Use
git clone https://github.com/Geoking2104/laya-onnx && cd laya-onnx
python benchmarks/evaluate.py receptron/laya-onnx --eval decisions.jsonl
License
Apache-2.0.