Laya on ONNX Runtime
ONNX is how most non-Python Laya runtimes work. An exported graph plus the tokenizer and calibration config is enough to answer typed questions with ONNX Runtime, and several projects publish ready-made exports so you can skip the PyTorch conversion step.
211 projects
Laya-Engine
Ydjin1984
Runs local Laya typed-decision models through Go and ONNX Runtime with a plugin and ZCode skill
reflex-hooks-oss
lia210350
A Node provider runs the Laya decision model locally through ONNX for reflex-hooks
laya-onnx-bench
gdelatournelle
Provides a reproducible evaluation set for Laya's ONNX decision backend
meldecision
meldltd
Serves Laya decision models through a GoFiber API using ONNX Runtime
laya-web
nvkudva
Runs a quantized Laya decision model entirely in the browser using ONNX Runtime Web
laya-web-poc
alexander-voronkov
A browser prototype runs a quantized Laya model locally for typed question answering
laya-bot-det
koteitan
Classifies Nostr authors as bots with Laya running in the browser
laya-int8
koteitan
Provides an int8-quantized Laya Multilingual ONNX model split into downloadable parts
laya-claude-plugin
noorforeverone
Provides a Claude Code plugin with local Laya decision tools and an MCP server
laya-onnx-runtime
zenryokukikai
Ports the Laya multilingual decision model to CPU-only ONNX Runtime
rsdecider-inference
House-of-Imaginations
Runs Laya decision models in a Rust server using ONNX Runtime
laya
waqas-duck
Runs the Laya decision model from Node.js and TypeScript using ONNX Runtime
laya-onnx
Geoking2104
Runs Laya decision models with ONNX Runtime and provides export, inference, and benchmark tools
laya-fastapi
remominor
Serves Laya typed decisions through a local FastAPI and ONNX Runtime deployment
laya-review
x007007007
Provides local-first code review using Laya decision rules through ONNX Runtime
laya-snapdragon
piffie
Runs Laya typed decisions on Snapdragon X NPUs through ONNX Runtime and Qualcomm QNN
laya-models
dockndevai
Provides quantized ONNX builds of Laya for browser inference
laya-hexagon-npu
EricYu123456
Deploys Laya inference on Qualcomm Hexagon NPU using ONNX Runtime
laya-vs-llms
Ujjwal3115
Benchmarks Laya against hosted language models on developer commit triage and CI safety decisions
vybir
Galactic717
Runs Laya locally with conformal error guarantees and includes score-based game-learning demos
laya
EduardoGHdez
A Ruby library runs the Laya decision model locally with ONNX Runtime
laya-s-dungeon
ValchanOficial
A tactical auto-battler that uses Laya through ONNX Runtime to choose actions each turn
layar
nullean
A .NET port of Laya provides ONNX and TorchSharp inference backends and CLI tools
laya-go
metalagman
Provides an embeddable Go runtime for local Laya inference and typed decision routing
Use a pre-converted export
inferenceprince/laya-onnx is an fp16 export of the English checkpoint. From its model card:
pip install onnxruntime huggingface_hub tokenizers numpy
hf download inferenceprince/laya-onnx --local-dir laya-onnx
The card includes a full Python example that builds the prompt, runs the graph and applies the fitted temperature. It reports load-to-first-answer of 3 to 5 s against 25 to 35 s for PyTorch on an Intel i5-14400F. The official package also has a laya[onnx] extra with an ONNXAgent class in laya.onnx_agent.
INT8 on CPU
edgejev converts Laya to ONNX, quantizes it to INT8 and serves it:
uv tool install "edgejev[build]"
edgejev build --backend laya --out ./jev-int8
Its README reports 15.6 ms per question for the INT8 multilingual model on a 4 vCPU Xeon (Cascade Lake) and 32.1 ms in fp32, with the model shrinking from 1290 MB to 324 MB. The same table shows AG News accuracy dropping from 92.8% to 91.2%.
ONNX in other languages
- Node.js: @receptron/laya, using receptron/laya-onnx.
- Java: Laya4j.
- Go: laya-onnx (MstyAI).
- Ruby: ruby-laya and laya (EduardoGHdez).
- Windows GPUs through DirectML: laya-windows.
- Local server: ollaya runs ONNX Runtime on CPU and CUDA.
- Browser: layaForWeb with ONNX Runtime Web.
Caveats
The graph returns raw logits. Divide by the fitted temperature from rl_agent_config.json before the softmax, or the probabilities mean nothing. Quantized builds drift from PyTorch: the layaForWeb README reports 97.9% top-answer agreement for its int8 build, and it notes that its confidence values are approximate because calibration was fitted on the full-precision model.
More ways to use Laya