laya-onnx
A ONNX build of laya, for running typed decisions on runtimes without PyTorch instead of a hosted API.
Community card
What this is
A repackaged build of laya, not a separate model. The weights are the same; what changes is the runtime you can put them in and the hardware that will hold them.
How to run it
ONNX Runtime
An ONNX export loads without PyTorch, which matters for slim containers and for browser or edge runtimes. Full ONNX Runtime guide.
pip install onnxruntime huggingface_hubWhat we have not measured
Everything. We have not run this model on our frozen test split, so we have no accuracy, no calibration error and no risk and coverage curve for it. The facts on this page come from its own repository metadata, read on 20 September 2026, and are accurate as far as that goes and no further. The one model we have measured end to end is Jev.
Sources
Every fact on this page traces to one of these, checked on the date shown. Download and like counts move; the rest of it should not.
- Hugging Face · Mattepiu/laya-onnxchecked 20 September 2026
Page last verified 20 September 2026.
A public number is a shortlist, not a decision
The only benchmark that settles which model you ship is one built from your own historical decisions. We freeze that test set, run the candidates against it, and hand back the threshold your error budget supports.