rex

Model · Text classification

laya-multilingual

Convai Innovations

Non-autoregressive System 1 decision model covering 100+ languages. Give it a state (text, email, ticket, or JSON) and typed questions; it returns typed answers with probabilities in a single forward pass. No text generation, so nothing to parse and nothing to hallucinate. Part of the Laya family — use this checkpoint for anything that is not English. Since laya 0.3.13 the default Router() keeps both english and this checkpoint resident, so a mixed workload no longer swaps checkpoints on every language change. For a server, load them up front so even the first request of each language is just a forward pass: router.attach("multilingual", agent) registers an Agent you already built, so a…

Laya typed decisions on Apple Silicon, running on the Core AI runtime — the successor to Core ML. This is a.aimodel asset exported from via Apple's coreai-torch bridge. It outputs choice / score / noul probabilities (and RL action logits) with zero generated tokens and no PyTorch, Core ML, Transformers, or cloud API at inference time. macOS 27+ (Core AI runtime), Python 3.10+. Validated on M3 Max / macOS 27.2. Validate the download end-to-end (all three specializations, timing, contract checks): Snake demo with the model (terminal game, reuses the laya-coreml UI + safety shield; automatically uses the B3 asset when present for ~2x game throughput): ~3× faster per pass than the fastest Core…

Model · Text classification

laya-pt-es-typed

Telepatia

This checkpoint fine-tunes convaiinnovations/laya-multilingual for native choice, score, and noul decisions in Portuguese and Spanish. It keeps the original 322M-parameter mmBERT architecture. It adds no inference component and does not generate text. It returns typed answers and probabilities in one forward pass. This is a text model. Inference takes a textual state plus typed questions. The second training stage used text decisions derived from public speech corpora, but this checkpoint does not accept audio by itself. The separate audio projector is not included. The official Laya SDK defines these primitives as follows: - choice: selects one key from a runtime-defined criteria object.…

Non-autoregressive System 1 decision model covering 100+ languages. Give it a state (text, email, ticket, or JSON) and typed questions; it returns typed answers with probabilities in a single forward pass. No text generation, so nothing to parse and nothing to hallucinate. Part of the Laya family — use this checkpoint for anything that is not English. The default Router() keeps both english and this checkpoint resident, so a mixed workload no longer swaps checkpoints on every language change. For a server, load them up front so even the first request of each language is just a forward pass: router.attach("multilingual", agent) registers an Agent you already built, so a process that loaded…

Classifies GitHub issues written in any language as bug, feature, question or docs. A fine-tune of Laya multilingual (mmBERT-base) used by the laya-triage GitHub Action for non-English issues, next to the English model laya-triage-en. The same 500 NLBSE'23 validation issues, machine-translated with NLLB-200 into 13 languages. Accuracy (±3 points per language): laya-triage and Jev are within noise of each other across languages; both are far ahead of the untuned base. Translations can flatter a model trained on translations, so we also checked real issues: on 367 non-English issues opened in 2026 (never seen, written by people, not translated) accuracy went from 47.1% to 65.7%. Use it…

Fine-tune of convaiinnovations/laya-multilingual (Apache-2.0) for prompt-injection and jailbreak detection. The base model is mmBERT, vocab 256k. Code: 3p3r/sentinel-laya. The English checkpoint is a different model: 3p3r/sentinel-laya. This revision starts from the inject-label checkpoint and adds a round on 3p3r/short-role-attacks, a synthetic English and German set of short role swaps and short orders, each with a benign twin. The five evaluation sets below were not part of training. Noul temperature is 2.2534, kept from the first revision. Threshold is 0.5. Positive class: jailbreak or prompt injection. Metric: Binary F1. Same prompts as the English card, one RTX 3090, batch size 64.…