layaLaya is an Apache-2.0 multilingual non-autoregressive decision model that answers typed questions (choices, scores, booleans) over text or JSON states with calibrated probabilities in a single ~33 ms forward pass, auto-routing across three checkpoints covering 100+ languages.
openjevopenjev fine-tunes Qwen3.5 into a zero-shot NLI cross-encoder (4B text+image v2, plus a 35B-A3B MoE variant) that scores premise–hypothesis pairs as entailment/contradiction/neutral — one primitive for reranking, answer grading, content guarding, and driving real-time game agents like Doom and Minecraft.
cua-s1-formscua-s1-forms is a 706K-parameter single-pass option scorer that maps a GUI form element plus typed candidates (fill each extracted entity, check, click, skip) to per-option probabilities, letting cua-driver fill and submit forms without an autoregressive LLM.
decider-2bdecider-2b is a 1.9B-parameter model that returns calibrated probability distributions over explicit option lists for multiple typed questions in one forward pass—no text generation—for fast routing, classification, judgments, and agent decisions.
open-jev-deberta-v3-largeA DeBERTa-v3-large encoder that maps one input state plus any number of typed questions (choice, ordered score, or yes/no) to calibrated per-question probability distributions in a single forward pass, reaching 0.854 in-domain accuracy at 0.022 ECE with zero structured-output errors.
rlcd-modernbert-151mA 151M-parameter ModernBERT-based decision engine delivering calibrated choices, scores, and probabilities—plus an explicit abstention slot—in a single ~35ms non-autoregressive forward pass, deployable in-browser via WebGPU/WASM or via ONNX for edge inference.
Jeff-1Jeff-1 is an Apache-2.0 LoRA adapter for Qwen3-4B-Instruct-2507 that scores caller-supplied labels to return typed decisions—choice, yes/no, and ordinal scores with probabilities and confidence—for local inference tasks like fact-checking without parsing generated text.
jev-schema-scorer-deberta-v3-largeA fine-tuned DeBERTa-v3-large encoder with a scalar head that scores (state, question + candidate) pairs, decoding grouped logits via softmax into choice, boolean (noul), and ordinal score answers—reading criteria and option ids at inference time so one checkpoint handles new label sets without retraining.
gliner2.5-cua-grounder-macos-v1A merged FP32 GLiNER2.5 fine-tune that chooses an action ID, `reobserve`, or `abstain` from a bounded action menu for local macOS CUA automation—without screenshots or tool calls—and is verified on browser DOM and native AppKit fixtures with low-latency MPS inference.
laya-groundedA fine-tune of the laya typed-decision model that improves grounding on explicitly stated facts, consistency between logical inverses, and probability calibration, at the cost of worse phishing detection and option-name routing stability.
chessjev-minilm-v1A chess option scorer that finetunes MiniLM-L6 with an attention head to emit logits for all legal moves from a FEN context in one forward pass, distilled from Stockfish 19 (0.445 teacher agreement, 0.667 on tactics) for fast move ranking rather than verified playing strength.