chrisxthe's repositories

ai-economist

Foundation is a flexible, modular, and composable framework to model socio-economic behaviors and dynamics with both agents and governments. This framework can be used in conjunction with reinforcement learning to learn optimal economic policies, as done by the AI Economist (https://www.einstein.ai/the-ai-economist).

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Asspp

The App Store for your multi-account eco system.

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Auto-GPT

An experimental open-source attempt to make GPT-4 fully autonomous.

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awesome-immigration

An Awesome list of long-term visas

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bilibot

A local chatbot fine-tuned by bilibili user comments.

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BLOOM_Examples

Some quick BLOOM LLM examples

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bypass-paywalls-chrome

Bypass Paywalls web browser extension for Chrome and Firefox.

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ChatGPT

🔮 ChatGPT Desktop Application (Mac, Windows and Linux)

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chatgpt_academic

科研工作专用ChatGPT拓展,特别优化学术Paper润色体验,支持自定义快捷按钮,支持markdown表格显示,Tex公式双显示,代码显示功能完善,新增本地Python工程剖析功能/自我剖析功能

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chatgpt_system_prompt

A collection of GPT system prompts and various prompt injection/leaking knowledge.

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ColossalAI

Making large AI models cheaper, faster and more accessible

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Deep-Reinforcement-Learning-Algorithms-with-PyTorch

PyTorch implementations of deep reinforcement learning algorithms and environments

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dingdong_monitor

叮咚买菜运力监控

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hugo

The world’s fastest framework for building websites.

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hugo-academic

📝 The website builder for Hugo. Build and deploy a beautiful website in minutes!

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kkndme_tianya

天涯 kkndme 神贴聊房价

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manim

Animation engine for explanatory math videos

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mlfinlab

Package based on the work of Dr Marcos Lopez de Prado regarding his research with respect to Advances in Financial Machine Learning

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neat-python

Python implementation of the NEAT neuroevolution algorithm

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research

Contains all the Jupyter Notebooks used in our research.

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Ryujinx

Experimental Nintendo Switch Emulator written in C#

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sample-market-maker

Sample BitMEX Market Making Bot

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stockpredictionai

In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.

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street-fighter-ai

This is an AI agent for Street Fighter II Champion Edition.

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tdl

📥 A Telegram tookit written in Golang

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telegram_media_downloader

Download media files from a telegram conversation/chat/channel up to 2GiB per file

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trackerslist

Updated list of public BitTorrent trackers

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V2rayU

V2rayU,基于v2ray核心的mac版客户端,用于科学上网,使用swift4.2编写,支持vmess,shadowsocks,socks5等服务协议,支持订阅, 支持二维码,剪贴板导入,手动配置,二维码分享等

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whisper

Robust Speech Recognition via Large-Scale Weak Supervision

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