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TradingAgents: Multi-Agents LLM Financial Trading Framework
Measuring Massive Multitask Language Understanding | ICLR 2021
Beyond the Imitation Game collaborative benchmark for measuring and extrapolating the capabilities of language models
New repo collection for NVIDIA Cosmos: https://github.com/nvidia-cosmos
code for deep learning courses
Modeling, training, eval, and inference code for OLMo
A starting point for developing your own plug-in for Auto-GPT
OpenAssistant is a chat-based assistant that understands tasks, can interact with third-party systems, and retrieve information dynamically to do so.
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.
🐙 Guides, papers, lessons, notebooks and resources for prompt engineering, context engineering, RAG, and AI Agents.
An Extensible Toolkit for Finetuning and Inference of Large Foundation Models. Large Models for All.
Source code for the X Recommendation Algorithm
A Unified Semi-Supervised Learning Codebase (NeurIPS'22)
A playbook for systematically maximizing the performance of deep learning models.
A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training
A high-performance, zero-overhead, extensible Python compiler with built-in NumPy support
⚡️ Python client for the unofficial ChatGPT API with auto token regeneration, conversation tracking, proxy support and more.
Code for Cicero, an AI agent that plays the game of Diplomacy with open-domain natural language negotiation.
YOLO9000: Better, Faster, Stronger - Real-Time Object Detection. 9000 classes!
Repo for reproduction of sequential social dilemmas
PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice （『飞桨』核心框架，深度学习&机器学习高性能单机、分布式训练和跨平台部署）
PaddleFormers is an easy-to-use library of pre-trained large language model zoo based on PaddlePaddle.
Multi-Joint dynamics with Contact. A general purpose physics simulator.
Training and serving large-scale neural networks with auto parallelization.