Non-autoregressive System 1 decision engine. Typed choice, score and yes/no decisions over any text in a single forward pass, in 100+ languages, with a router that picks the right checkpoint per request.
The repository provides code for running inference and finetuning with the Meta Segment Anything Model 3 (SAM 3), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
Open-source, self-hosted Claude Code - a terminal AI assistant and the Python framework behind it. Tool-calling, sandboxed execution, multi-agent teams, skills, checkpoints, unlimited context - on Pydantic AI, any model.
AI multi-agent tool that turns research papers into cited commercialization and tech-transfer assessments: TRL, patent landscape, market and risks. CrewAI + FastAPI, with a reproducible benchmark.
Orbax provides common checkpointing and persistence utilities for JAX users
Official implementation of PhiZero: A World Model Built Around Physical Language. Code and checkpoints coming soon.
Flex-Ο: A multi-stream world-action model with compute flexibility: one checkpoint that deploys as a VLA, a full world model, or anything in between.
Local-first research memory for Codex: checkpoints, progress ledgers, and Markdown/JSON paper notes. Early alpha.
Closed-loop fault localization and checkpoint recovery for LLM Pre-training
AI coding agent with one Python core and three front-ends β headless CLI, Textual TUI, and an Electron desktop. Works with any OpenAI-compatible API, with risk-tiered permissions, event-sourced replayable sessions, and a fail-closed OS-level sandbox.
A minimal, readable agent-framework kernel β understand how LangGraph/ADK work under the hood. 1800θ‘代η η agent ζ‘ζΆε ζ ΈοΌηθ§£ LangGraph/ADK εΊε±ηε·₯δ½εη
Dexterous pen spinning and Rubik's cube: sim environments, zero-shot scripts, trained checkpoints
AtlasAgent - an auditable AI agent control plane: evidence-backed memory, governed tool runtime, checkpoint DAG recovery, and a 55-chapter engineering tutorial. FastAPI / Next.js PWA / Textual TUI
TempoVista is the official implementation of Dyn-3D, a benchmark and training pipeline for 3D spatial reasoning in vision-language models. The release contains frame-selection tools, SFT and Kinematic-GSPO training code, benchmark evaluation scripts, Dyn-3D annotations, and checkpoints for Qwen3-VL and InternVL3.5.
Hangzhou Mahjong training and evaluation framework with public-information Transformers, paired branch reinforcement learning, and the r2600 checkpoint.
Autonomous experiment-pipeline orchestrator: versioned research-plan DSL with dependency DAGs, deterministic checkpoint/resumable executor, tamper-evident provenance ledger, UCB1/Thompson schedulers with measured regret against synthetic oracles, ablation bookkeeping, offline report synthesis. NumPy core, CPU-only torch extra.
InJepa: Intention First Latent State Planning with Coupled JEPAs for Visual Navigation. Code, Clean150 tasks and E12 checkpoint.
DeepSeek-V4.1-Flash on two NVIDIA DGX Sparks: EXL3 weights from the official checkpoint, upstream vLLM with our patches and decode kernels
Serve Ornith-1.5-35B-A3B (NVFP4 + in-checkpoint MTP, 256k ctx) on one DGX Spark β vLLM b12x recipe plus CUDA-graph fixes.