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AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Robust Speech Recognition via Large-Scale Weak Supervision
🌐 Make websites accessible for AI agents. Automate tasks online with ease.
Models and examples built with TensorFlow
RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context layer for LLMs
A natural language interface for computers
openpilot is an operating system for robotics. Currently, it upgrades the driver assistance system on 300+ supported cars.
No fortress, purely open ground. OpenManus is Coming.
LlamaIndex is the leading document agent and OCR platform
Framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks.
A Simple and Universal Swarm Intelligence Engine, Predicting Anything. 简洁通用的群体智能引擎，预测万物
A community-maintained Python framework for creating mathematical animations.
OpenAssistant is a chat-based assistant that understands tasks, can interact with third-party systems, and retrieve information dynamically to do so.
A toolkit for developing and comparing reinforcement learning algorithms.
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep lear…
A generative world for general-purpose robotics & embodied AI learning.
Open-sourced codes for MiniGPT-4 and MiniGPT-v2 (https://minigpt-4.github.io, https://minigpt-v2.github.io/)
Code for the paper "Language Models are Unsupervised Multitask Learners"
[NeurIPS'23 Oral] Visual Instruction Tuning (LLaVA) built towards GPT-4V level capabilities and beyond.
A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training
Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.