All decision model projects
2823 public apps, SDKs, integrations, demos and write-ups built on decision models. Projects with working code come first.
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Open multimodal decision model fine-tuned from Gemma 4 12B that returns option probabilities for text, image, audio and video questions.
ModelresearchPythonResearch router where a Qwen3-1.7B belief model scores intent candidates and a small policy decides to commit, retrieve more or hand off.
ModelresearchPythonReinforcement-learning lab where cached Jev judgments act as reward signals for DQN agents on four classic control and grid games.
ModelresearchPythonPreprint survey of Jev-style typed decision models: their research roots, adaptation costs and what current evidence supports.
ModelresearchOpen infrastructure for training, evaluating and deploying System 1 decision models, with calibrated LoRA checkpoints on a 27B backbone.
ModelresearchPythonOpen stack to synthesise decision data, train and calibrate a Qwen3.5-0.8B scorer, evaluate on Mind2Web and serve Jev-style.
ServiceresearchPythonTraining library for a small one-pass model that scores a changing list of text options and returns a probability per option.
LibraryresearchPythonOpen Jev-style 0.6B decision model plugged into BlitzRank and Reranker-Guided Search, scoring k candidates per match in one pass.
ServiceresearchPythonIndependent measurements of Jev versus open Laya on typed decisions, plus a local-first cascade that matches Jev at 1.8x speed.
ServiceresearchPythonClojure System One engine on Jolt that routes typed questions to Laya encoders, a llama.cpp 'thinker', Clef or TinyDecide.
ModelresearchClojureReproduction of Jev's decision layer on any Qwen model: serves /v1/systemone by scoring option tokens, with no training or generation.
ServiceresearchPythonOffline System One server that answers Jev-format questions with small open models, wire-compatible with TypeSafe's official SDK.
ServiceresearchPythonImage-plus-text decision model on Qwen3-VL-2B with LoRA and an answer head that returns one probability per option.
ModelresearchPythonOpen MiniCPM5-2B decision model serving /v1/systemone: typed choice, noul and score probabilities in one forward pass.
ModelresearchPythonJev-style replica: frozen Qwen3-1.7B plus a ~0.8M-parameter trained head returns calibrated Choice, Boolean and Score distributions.
ServiceresearchPythonBrowser lab and TypeSafe-shaped API for asking typed questions of a Nemotron diffusion model and inspecting the distributions.
ModelresearchPythonnev-lite: 11.8M-parameter static-embedding decision head that scores fixed option sets with no transformer pass at inference.
ModelresearchPythonOmniJev: omni-modal 4B decision model answering typed questions about images, video, screens and robot scenes in one pass.
ModelresearchPythonOpen 150M encoder that answers noul, choice and score questions in one pass, trainable on a free Colab T4 in about 30 minutes.
ModelresearchPythonTwo frozen open models answer yes/no per exam option; their agreement drives an auto-release gate and a conformal candidate set.
ServiceresearchPythonspark-s1: local Jev-inspired decision models on Qwen3.5-4B for NVIDIA DGX Spark, trained on code- and solver-labelled decision rows.
ModelresearchPythonDrop-in faster backend for Open-Jev-27B using custom CUDA kernels, a prefix tree and CUDA graphs: about 6x lower JevBench latency.
ModelresearchPythonVerdict: 151M ModernBERT/GLiClass non-autoregressive decision models with calibration heads, reporting wins over Jev and Laya.
ModelresearchPythonResearch toolkit that encodes an image once and answers several typed questions from a shared distribution, plus OpenJev-0.6B text models.
ModelresearchPythonResearch engine for local System One decisions via llama.cpp logits projection with Qwen, running sub-second on a 4 GB laptop GPU.
ModelresearchPythonHugging Face Space for parallel constrained decoding on Apple Silicon: fills multi-field JSON schemas in parallel with field confidence.
ModelresearchPythonPhocinae Largha: 144.3M bilingual English/Chinese decision model on mmBERT-small with calibrated Choice, Score and Noul in one pass.
ModelresearchPythonPlayJev: Qwen3.5-0.8B fine-tuned to play ten browser games from raw pixels, one forward pass per move with a probability per option.
ServiceresearchPythonOpen decision models fine-tuned from Qwen at 0.8B to 9B that return a choice and per-option probabilities for Choice, Noul and Score.
ModelresearchPythonPrototype Jev-style decision model on Qwen3.5-0.8B using prefix-fork execution to answer typed questions in one pass without generation.
ModelresearchPython