typed/recipes
Models / Laya

Laya

An open-weight model that answers the same three question types as Jev and runs on your own GPU or CPU. Three checkpoints ship: English (421M), multilingual for 100+ languages (322M), and one tuned on typed decisions (421M).

What it's good at

  • Runs locally, so your data never leaves your server. Air-gapped deployment works.
  • You can fine-tune it on your own labels.
  • No per-call fee.
  • Multilingual checkpoint with automatic routing by script.

Limits and caveats

  • The base model is close to chance zero-shot: 0.362 on the typed-decisions benchmark against a 0.318 random baseline.
  • The headline 0.766 accuracy comes from a checkpoint fine-tuned on that same benchmark's training split.
  • Probabilities are over-confident until you fit temperatures on your own data.
  • Convai's own README calls it a fast base to specialise, not a zero-shot decision engine.
  • Its “6–8× faster than Jev” compares local GPU inference against Jev's network round trip.

Directory entries using Laya

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