What this is
recmeets-laya-words is a typed-decision model: given a document and a closed set of options, it returns one of those options with a probability across the whole set rather than free text.
Its card lists training data: google/fleurs, fsicoli/common_voice_22_0, aangelakis/STOMA. That matters when you read any benchmark number about it, because a model tuned on a benchmark's own training split has an advantage over one that has never seen it.
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_hubA 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.