LLMForEverybody

LLMForEverybody is a comprehensive repository covering various aspects of large language models (LLMs) including pre-training, architecture, optimizers, activation functions, attention mechanisms, tokenization, parallel strategies, training frameworks, deployment, fine-tuning, quantization, GPU parallelism, prompt engineering, agent design, RAG architecture, enterprise deployment challenges, evaluation metrics, and current hot topics in the field. It provides detailed explanations, tutorials, and insights into the workings and applications of LLMs, making it a valuable resource for researchers, developers, and enthusiasts interested in understanding and working with large language models.

AutoPilot Observability (APO) is an out-of-the-box observability platform that provides one-click installation and ready-to-use capabilities. APO's OneAgent supports one-click configuration-free installation of Tracing probes, collects application fault scene logs, infrastructure metrics, network metrics of applications and downstream dependencies, and Kubernetes events. It supports collecting causality metrics based on eBPF implementation. APO integrates OpenTelemetry probes, otel-collector, Jaeger, ClickHouse, and VictoriaMetrics, reducing user configuration work. APO innovatively integrates eBPF technology with the OpenTelemetry ecosystem, significantly reducing data storage volume. It offers guided troubleshooting using eBPF technology to assist users in pinpointing fault causes on a single page.

AI-YinMei is an AI virtual anchor Vtuber development tool (N card version). It supports fastgpt knowledge base chat dialogue, a complete set of solutions for LLM large language models: [fastgpt] + [one-api] + [Xinference], supports docking bilibili live broadcast barrage reply and entering live broadcast welcome speech, supports Microsoft edge-tts speech synthesis, supports Bert-VITS2 speech synthesis, supports GPT-SoVITS speech synthesis, supports expression control Vtuber Studio, supports painting stable-diffusion-webui output OBS live broadcast room, supports painting picture pornography public-NSFW-y-distinguish, supports search and image search service duckduckgo (requires magic Internet access), supports image search service Baidu image search (no magic Internet access), supports AI reply chat box [html plug-in], supports AI singing Auto-Convert-Music, supports playlist [html plug-in], supports dancing function, supports expression video playback, supports head touching action, supports gift smashing action, supports singing automatic start dancing function, chat and singing automatic cycle swing action, supports multi scene switching, background music switching, day and night automatic switching scene, supports open singing and painting, let AI automatically judge the content.

LLMLanding is a repository focused on practical implementation of large models, covering topics from theory to practice. It provides a structured learning path for training large models, including specific tasks like training 1B-scale models, exploring SFT, and working on specialized tasks such as code generation, NLP tasks, and domain-specific fine-tuning. The repository emphasizes a dual learning approach: quickly applying existing tools for immediate output benefits and delving into foundational concepts for long-term understanding. It offers detailed resources and pathways for in-depth learning based on individual preferences and goals, combining theory with practical application to avoid overwhelm and ensure sustained learning progress.

AIBotPublic is an open-source version of AIBotPro, a comprehensive AI tool that provides various features such as knowledge base construction, AI drawing, API hosting, and more. It supports custom plugins and parallel processing of multiple files. The tool is built using bootstrap4 for the frontend, .NET6.0 for the backend, and utilizes technologies like SqlServer, Redis, and Milvus for database and vector database functionalities. It integrates third-party dependencies like Baidu AI OCR, Milvus C# SDK, Google Search, and more to enhance its capabilities.

llm-resource is a comprehensive collection of high-quality resources for Large Language Models (LLM). It covers various aspects of LLM including algorithms, training, fine-tuning, alignment, inference, data engineering, compression, evaluation, prompt engineering, AI frameworks, AI basics, AI infrastructure, AI compilers, LLM application development, LLM operations, AI systems, and practical implementations. The repository aims to gather and share valuable resources related to LLM for the community to benefit from.

AI Paint Today is an API server repository that allows users to record their emotions and daily experiences, and based on that, AI generates a beautiful picture diary of their day. The project includes features such as generating picture diaries from written entries, utilizing DALL-E 2 model for image generation, and deploying on AWS and Cloudflare. The project also follows specific conventions and collaboration strategies for development.

KrillinAI is a video subtitle translation and dubbing tool based on AI large models, featuring speech recognition, intelligent sentence segmentation, professional translation, and one-click deployment of the entire process. It provides a one-stop workflow from video downloading to the final product, empowering cross-language cultural communication with AI. The tool supports multiple languages for input and translation, integrates features like automatic dependency installation, video downloading from platforms like YouTube and Bilibili, high-speed subtitle recognition, intelligent subtitle segmentation and alignment, custom vocabulary replacement, professional-level translation engine, and diverse external service selection for speech and large model services.

The Awesome ChatGPT Chinese Guide project aims to help Chinese users understand and use ChatGPT. It collects various free and paid ChatGPT resources, as well as methods to communicate more effectively with ChatGPT in Chinese. The repository contains a rich collection of ChatGPT tools, applications, and examples.

Long-Novel-GPT is a long novel generator based on large language models like GPT. It utilizes a hierarchical outline/chapter/text structure to maintain the coherence of long novels. It optimizes API calls cost through context management and continuously improves based on self or user feedback until reaching the set goal. The tool aims to continuously refine and build novel content based on user-provided initial ideas, ultimately generating long novels at the level of human writers.

ChatGPT-PLUS is an open-source AI assistant solution based on AI large language model API, with a built-in operational management backend for easy deployment. It integrates multiple large language models from platforms like OpenAI, Azure, ChatGLM, Xunfei Xinghuo, and Wenxin Yanyan. Additionally, it includes MidJourney and Stable Diffusion AI drawing features. The system offers a complete open-source solution with ready-to-use frontend and backend applications, providing a seamless typing experience via Websocket. It comes with various pre-trained role applications such as Xiaohongshu writer, English translation master, Socrates, Confucius, Steve Jobs, and weekly report assistant to meet various chat and application needs. Users can enjoy features like Suno Wensheng music, integration with MidJourney/Stable Diffusion AI drawing, personal WeChat QR code for payment, built-in Alipay and WeChat payment functions, support for various membership packages and point card purchases, and plugin API integration for developing powerful plugins using large language model functions.

GeekAI is an open-source AI assistant solution based on AI large language model API, featuring a complete system with ready-to-use front-end and back-end management, providing a seamless typing experience via Websocket. It integrates various pre-trained character applications like Xiaohongshu writing assistant, English translation master, Socrates, Confucius, Steve Jobs, and weekly report assistant. The tool supports multiple large language models from platforms like OpenAI, Azure, Wenxin Yanyan, Xunfei Xinghuo, and Tsinghua ChatGLM. Additionally, it includes MidJourney and Stable Diffusion AI drawing functionalities for creating various artworks such as text-based images, face swapping, and blending images. Users can utilize personal WeChat QR codes for payment without the need for enterprise payment channels, and the tool offers integrated payment options like Alipay and WeChat Pay with support for multiple membership packages and point card purchases. It also features a plugin API for developing powerful plugins using large language model functions, including built-in plugins for Weibo hot search, today's headlines, morning news, and AI drawing functions.

FisherAI is a Chrome extension designed to improve learning efficiency. It supports automatic summarization, web and video translation, multi-turn dialogue, and various large language models such as gpt/azure/gemini/deepseek/mistral/groq/yi/moonshot. Users can enjoy flexible and powerful AI tools with FisherAI.

Stable Diffusion is a text-to-image AI model that can generate realistic images from a given text prompt. It is a powerful tool that can be used for a variety of creative and practical applications, such as generating concept art, creating illustrations, and designing products. Stable Diffusion is also a great tool for learning about AI and machine learning. This repository contains a collection of tutorials and resources on how to use Stable Diffusion.

This repository documents how to optimize common algorithms based on CUDA. It includes subdirectories with code implementations for specific optimizations. The optimizations cover topics such as compiling PyTorch from source, NVIDIA's reduce optimization, OneFlow's elementwise template, fast atomic add for half data types, upsample nearest2d optimization in OneFlow, optimized indexing in PyTorch, OneFlow's softmax kernel, linear attention optimization, and more. The repository also includes learning resources related to deep learning frameworks, compilers, and optimization techniques.

EZ-Work AI Document Translation is an AI document translation assistant accessible to everyone. It enables quick and cost-effective utilization of major language model APIs like OpenAI to translate documents in formats such as txt, word, csv, excel, pdf, and ppt. The tool supports AI translation for various document types, including pdf scanning, compatibility with OpenAI format endpoints via intermediary API, batch operations, multi-threading, and Docker deployment.

This repository contains assets related to AI/ML workloads on Google Kubernetes Engine (GKE). Run optimized AI/ML workloads with Google Kubernetes Engine (GKE) platform orchestration capabilities. A robust AI/ML platform considers the following layers: Infrastructure orchestration that support GPUs and TPUs for training and serving workloads at scale Flexible integration with distributed computing and data processing frameworks Support for multiple teams on the same infrastructure to maximize utilization of resources

Ray is a unified framework for scaling AI and Python applications. It consists of a core distributed runtime and a set of AI libraries for simplifying ML compute, including Data, Train, Tune, RLlib, and Serve. Ray runs on any machine, cluster, cloud provider, and Kubernetes, and features a growing ecosystem of community integrations. With Ray, you can seamlessly scale the same code from a laptop to a cluster, making it easy to meet the compute-intensive demands of modern ML workloads.

Labelbox is a data-centric AI platform for enterprises to develop, optimize, and use AI to solve problems and power new products and services. Enterprises use Labelbox to curate data, generate high-quality human feedback data for computer vision and LLMs, evaluate model performance, and automate tasks by combining AI and human-centric workflows. The academic & research community uses Labelbox for cutting-edge AI research.

Deep Java Library (DJL) is an open-source, high-level, engine-agnostic Java framework for deep learning. It is designed to be easy to get started with and simple to use for Java developers. DJL provides a native Java development experience and allows users to integrate machine learning and deep learning models with their Java applications. The framework is deep learning engine agnostic, enabling users to switch engines at any point for optimal performance. DJL's ergonomic API interface guides users with best practices to accomplish deep learning tasks, such as running inference and training neural networks.

MLflow is a platform to streamline machine learning development, including tracking experiments, packaging code into reproducible runs, and sharing and deploying models. MLflow offers a set of lightweight APIs that can be used with any existing machine learning application or library (TensorFlow, PyTorch, XGBoost, etc), wherever you currently run ML code (e.g. in notebooks, standalone applications or the cloud). MLflow's current components are: * `MLflow Tracking `_: An API to log parameters, code, and results in machine learning experiments and compare them using an interactive UI. * `MLflow Projects `_: A code packaging format for reproducible runs using Conda and Docker, so you can share your ML code with others. * `MLflow Models `_: A model packaging format and tools that let you easily deploy the same model (from any ML library) to batch and real-time scoring on platforms such as Docker, Apache Spark, Azure ML and AWS SageMaker. * `MLflow Model Registry `_: A centralized model store, set of APIs, and UI, to collaboratively manage the full lifecycle of MLflow Models.

TT-NN is a python & C++ Neural Network OP library. It provides a low-level programming model, TT-Metalium, enabling kernel development for Tenstorrent hardware.

Burn is a new comprehensive dynamic Deep Learning Framework built using Rust with extreme flexibility, compute efficiency and portability as its primary goals.

This repository contains reference architectures and test cases for distributed model training with Amazon SageMaker Hyperpod, AWS ParallelCluster, AWS Batch, and Amazon EKS. The test cases cover different types and sizes of models as well as different frameworks and parallel optimizations (Pytorch DDP/FSDP, MegatronLM, NemoMegatron...).

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.