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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.
OpenMMLab Detection Toolbox and Benchmark
The open source AI engineering platform for agents, LLMs, and ML models. MLflow enables teams of all sizes to debug, evaluate, monitor, and optimize production-quality AI applications while controlling costs and managing access to models and data.
FinRL®: Financial Reinforcement Learning. 🔥
Nano vLLM
Production ready toolkit to run AI locally
simple neural network library in C99
MarS: a Financial Market Simulation Engine Powered by Generative Foundation Model
PGPortfolio: Policy Gradient Portfolio, the source code of "A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem"(https://arxiv.org/pdf/1706.10059.pdf).
An open source tool to quantify the world
Hopsworks - Data-Intensive AI platform with a Feature Store
Scalable, event-driven, deep-learning-friendly backtesting library
This repository introduces PIXIU, an open-source resource featuring the first financial large language models (LLMs), instruction tuning data, and evaluation benchmarks to holistically assess financial LLMs. Our goal is to continually push forward the open-source development of financial artificial intelligence (AI).
💃 Free CC0 mannequin pose reference library for AI image tools (Nano Banana, ChatGPT, ComfyUI, Midjourney) — 250+ poses × 5 angles in line art, names in ja/zh/en/ko
A self-hosted AI media studio with an independent local macOS workspace. Bring your own API keys.
Edit photos by describing the change, on your own GPU. A free, open-source alternative to Nano Banana and ChatGPT image editing: photos stay on your computer, no daily limit. One installer for Windows, Mac and Linux sets up the best open model (Qwen-Image 2.1). MCP server for AI agents.
Deep Reinforcement Learning for Financial Trading using Price Trailing @ ICASSP 2019
A Network Integration Approach for Drug-Target Interaction Prediction
Trust metadata for AI agents — a stamp costs ~15 tokens, re-verifying costs 15,000. Agents stamp what they verify; the next agent runs 'akf check' and builds on it. pip install akf