BadukMegapack is an installer for various AI Baduk (Go) programs, designed for baduk players who want to easily access and use a variety of baduk AI programs without complex installations. The megapack includes popular programs like Lizzie, KaTrain, Sabaki, KataGo, LeelaZero, and more, along with weight files for different AI models. Users can update their graphics card drivers before installation for optimal performance.

Lumi AI is a friendly AI sidekick with a human-like personality that offers features like file upload and analysis, web search, local chat storage, custom instructions, changeable conversational style, enhanced context retention, voice query input, and various tools. The project has been developed with contributions from a team of developers, designers, and testers, and is licensed under Apache 2.0 and MIT licenses.

A collection of papers and resources about Large Language Models (LLM) for Graph Learning (Graph). Integrating LLMs with graph learning techniques to enhance performance in graph learning tasks. Categorizes approaches based on four primary paradigms and nine secondary-level categories. Valuable for research or practice in self-supervised learning for recommendation systems.

This repository is dedicated to enhancing Language Model (LLM) reasoning with reinforcement learning (RL). It includes a collection of the latest papers, slides, and materials related to RL-based LLM reasoning, aiming to facilitate quick learning and understanding in this field. Starring this repository allows users to stay updated and engaged with the forefront of RL-based LLM reasoning.

A curated list of awesome Model Context Protocol (MCP) servers that enable AI models to securely interact with local and remote resources through standardized server implementations. The list focuses on production-ready and experimental servers extending AI capabilities through file access, database connections, API integrations, and other contextual services.

Awesome Text2SQL is a curated repository containing tutorials and resources for Large Language Models, Text2SQL, Text2DSL, Text2API, Text2Vis, and more. It provides guidelines on converting natural language questions into structured SQL queries, with a focus on NL2SQL. The repository includes information on various models, datasets, evaluation metrics, fine-tuning methods, libraries, and practice projects related to Text2SQL. It serves as a comprehensive resource for individuals interested in working with Text2SQL and related technologies.

This repository aims to promote global equality for individuals pursuing a PhD in NLP by providing resources and information on various aspects of the academic journey. It covers topics such as applying for a PhD, getting research opportunities, preparing for the job market, and succeeding in academia. The repository is actively updated and includes contributions from experts in the field.

cl-waffe2 is an experimental deep learning framework in Common Lisp, providing fast, systematic, and customizable matrix operations, reverse mode tape-based Automatic Differentiation, and neural network model building and training features accelerated by a JIT Compiler. It offers abstraction layers, extensibility, inlining, graph-level optimization, visualization, debugging, systematic nodes, and symbolic differentiation. Users can easily write extensions and optimize their networks without overheads. The framework is designed to eliminate barriers between users and developers, allowing for easy customization and extension.

Phi-3CookBook is a manual on how to use the Microsoft Phi-3 family, which consists of open AI models developed by Microsoft. The Phi-3 models are highly capable and cost-effective small language models, outperforming models of similar and larger sizes across various language, reasoning, coding, and math benchmarks. The repository provides detailed information on different Phi-3 models, their performance, availability, and usage scenarios across different platforms like Azure AI Studio, Hugging Face, and Ollama. It also covers topics such as fine-tuning, evaluation, and end-to-end samples for Phi-3-mini and Phi-3-vision models, along with labs, workshops, and contributing guidelines.

Awesome-LLM-Ensemble is a collection of papers on LLM Ensemble, focusing on the comprehensive use of multiple large language models to benefit from their individual strengths. It provides a systematic review of recent developments in LLM Ensemble, including taxonomy, methods for ensemble before, during, and after inference, benchmarks, applications, and related surveys.

Summary You is a tool that utilizes AI to summarize YouTube videos, articles, images, and documents. Users can set the length of the summary and have the option to listen to the summaries. The tool also includes a history section, intelligent paywall detection, OLED-Dark Mode, and a user-friendly Material Design 3 style UI with dynamic color themes. It uses GPT-3.5 OpenAI/Mixtral 8x7B Groq for summarization. The backend is implemented in Python with Chaquopy, and some UI designs and codes are borrowed from Seal Material color utilities.

Fast-stable-diffusion is a project that offers notebooks for RunPod, Paperspace, and Colab Pro adaptations with AUTOMATIC1111 Webui and Dreambooth. It provides tools for running and implementing Dreambooth, a stable diffusion project. The project includes implementations by XavierXiao and is sponsored by Runpod, Paperspace, and Colab Pro.

SGLang is a structured generation language designed for large language models (LLMs). It makes your interaction with LLMs faster and more controllable by co-designing the frontend language and the runtime system. The core features of SGLang include: - **A Flexible Front-End Language**: This allows for easy programming of LLM applications with multiple chained generation calls, advanced prompting techniques, control flow, multiple modalities, parallelism, and external interaction. - **A High-Performance Runtime with RadixAttention**: This feature significantly accelerates the execution of complex LLM programs by automatic KV cache reuse across multiple calls. It also supports other common techniques like continuous batching and tensor parallelism.

The 'awesome-AI4MolConformation-MD' repository focuses on protein conformations and molecular dynamics using generative artificial intelligence and deep learning. It provides resources, reviews, datasets, packages, and tools related to AI-driven molecular dynamics simulations. The repository covers a wide range of topics such as neural networks potentials, force fields, AI engines/frameworks, trajectory analysis, visualization tools, and various AI-based models for protein conformational sampling. It serves as a comprehensive guide for researchers and practitioners interested in leveraging AI for studying molecular structures and dynamics.

This repository is a collection of papers on Generative AI Machine Unlearning, categorized based on modality and applications. It includes datasets, benchmarks, and surveys related to unlearning scenarios in generative AI. The repository aims to provide a comprehensive overview of research in the field of machine unlearning for generative models.

BadukMegapack is an installer for various AI Baduk (Go) programs, designed for baduk players who want to easily access and use a variety of baduk AI programs without complex installations. The megapack includes popular programs like Lizzie, KaTrain, Sabaki, KataGo, LeelaZero, and more, along with weight files for different AI models. Users can update their graphics card drivers before installation for optimal performance.

YGO Agent is a project focused on using deep learning to master the Yu-Gi-Oh! trading card game. It utilizes reinforcement learning and large language models to develop advanced AI agents that aim to surpass human expert play. The project provides a platform for researchers and players to explore AI in complex, strategic game environments.

KaTrain is a tool designed for analyzing games and playing go with AI feedback from KataGo. Users can review their games to find costly moves, play against AI with immediate feedback, play against weakened AI versions, and generate focused SGF reviews. The tool provides various features such as previews, tutorials, installation instructions, and configuration options for KataGo. Users can play against AI, receive instant feedback on moves, explore variations, and request in-depth analysis. KaTrain also supports distributed training for contributing to KataGo's strength and training bigger models. The tool offers themes customization, FAQ section, and opportunities for support and contribution through GitHub issues and Discord community.

HybridAGI is the first Programmable LLM-based Autonomous Agent that lets you program its behavior using a **graph-based prompt programming** approach. This state-of-the-art feature allows the AGI to efficiently use any tool while controlling the long-term behavior of the agent. Become the _first Prompt Programmers in history_ ; be a part of the AI revolution one node at a time! **Disclaimer: We are currently in the process of upgrading the codebase to integrate DSPy**

The NZT Poker AI Bot is an advanced tool designed to revolutionize poker gameplay by providing comprehensive features to dominate 17 rooms with the Cash Fish Monitor. It offers detailed analysis of opponents' VPIP and PFR, extensive hand history database, opponent exploitation techniques, data-driven intelligence, player profiles, advanced neural network technology, expert training, continuous refinement, and cutting-edge algorithms for maximizing poker profits. Created by a team of poker experts, this AI tool continuously adapts to the latest poker strategies and utilizes state-of-the-art technology to enhance decision-making prowess.

Sweep is an AI junior developer that turns bugs and feature requests into code changes. It automatically handles developer experience improvements like adding type hints and improving test coverage.

The Teams AI Library is a software development kit (SDK) that helps developers create bots that can interact with Teams and Microsoft 365 applications. It is built on top of the Bot Framework SDK and simplifies the process of developing bots that interact with Teams' artificial intelligence capabilities. The SDK is available for JavaScript/TypeScript, .NET, and Python.

This guide is dedicated to Large Language Models (LLMs) that you can run on your home computer. It assumes your PC is a lower-end, non-gaming setup.

Supercharge WordPress Content Workflows and Engagement with Artificial Intelligence. Tap into leading cloud-based services like OpenAI, Microsoft Azure AI, Google Gemini and IBM Watson to augment your WordPress-powered websites. Publish content faster while improving SEO performance and increasing audience engagement. ClassifAI integrates Artificial Intelligence and Machine Learning technologies to lighten your workload and eliminate tedious tasks, giving you more time to create original content that matters.

Chatbot UI is an open-source AI chat app that allows users to create and deploy their own AI chatbots. It is easy to use and can be customized to fit any need. Chatbot UI is perfect for businesses, developers, and anyone who wants to create a chatbot.

BricksLLM is a cloud native AI gateway written in Go. Currently, it provides native support for OpenAI, Anthropic, Azure OpenAI and vLLM. BricksLLM aims to provide enterprise level infrastructure that can power any LLM production use cases. Here are some use cases for BricksLLM: * Set LLM usage limits for users on different pricing tiers * Track LLM usage on a per user and per organization basis * Block or redact requests containing PIIs * Improve LLM reliability with failovers, retries and caching * Distribute API keys with rate limits and cost limits for internal development/production use cases * Distribute API keys with rate limits and cost limits for students

uAgents is a Python library developed by Fetch.ai that allows for the creation of autonomous AI agents. These agents can perform various tasks on a schedule or take action on various events. uAgents are easy to create and manage, and they are connected to a fast-growing network of other uAgents. They are also secure, with cryptographically secured messages and wallets.

Griptape is a modular Python framework for building AI-powered applications that securely connect to your enterprise data and APIs. It offers developers the ability to maintain control and flexibility at every step. Griptape's core components include Structures (Agents, Pipelines, and Workflows), Tasks, Tools, Memory (Conversation Memory, Task Memory, and Meta Memory), Drivers (Prompt and Embedding Drivers, Vector Store Drivers, Image Generation Drivers, Image Query Drivers, SQL Drivers, Web Scraper Drivers, and Conversation Memory Drivers), Engines (Query Engines, Extraction Engines, Summary Engines, Image Generation Engines, and Image Query Engines), and additional components (Rulesets, Loaders, Artifacts, Chunkers, and Tokenizers). Griptape enables developers to create AI-powered applications with ease and efficiency.