Hugging Face 的真实世界机器人库,含模型、数据集与工具。
🔬 行业与科研 AI
金融、机器人、科学计算等垂直领域
多智能体大模型金融交易框架。
面向分析师与量化的开放金融数据平台。
LLM 驱动的多市场股票智能分析系统:多源行情、实时新闻、决策看板与自动推送,支持零成本定时运行。 LLM-powered multi-market stock analysis system with multi-source market data, real-time news, decision dashboard, automated notifications, and cost-free scheduled runs.
AI 对冲基金团队概念验证项目。
Qlib is an AI-oriented Quant investment platform that aims to use AI tech to empower Quant Research, from exploring ideas to implementing productions. Qlib supports diverse ML modeling paradigms, including supervised lea
Kronos: A Foundation Model for the Language of Financial Markets
"Vibe-Trading: Your Personal Trading Agent"
TimesFM (Time Series Foundation Model) is a pretrained time-series foundation model developed by Google Research for time-series forecasting.
Simulation platform for general-purpose robotics & embodied AI learning.
开源金融大语言模型。
The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement learning and imitation
DeepMind 的蛋白质结构预测开源实现。
A standard API for single-agent reinforcement learning environments, with popular reference environments and related utilities (formerly Gym)
Bayesian Modeling and Probabilistic Programming in Python
AI Toolkit for Healthcare Imaging
FinRobot: An Open-Source AI Agent Platform for Financial Applications using Large Language Models
Stanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages
Local-first healthcare AI: clinical NER and HIPAA PII de-identification on hardware you control. 2,200+ medical models, 35 model-backed PII languages, and Python, MLX, Android and browser runtimes. Apache-2.0 SDK.
Probabilistic time series modeling in Python
Webots Robot Simulator
TorchGeo: datasets, samplers, transforms, and pre-trained models for geospatial data
A flexible, high-performance 3D simulator for Embodied AI research.
Open-source deep-learning framework for building, training, and fine-tuning deep learning models using state-of-the-art Physics-ML methods