LLM Learning Database is a comprehensive repository dedicated to AI large models, offering a curated collection of resources covering fundamental knowledge, cutting-edge technologies, and practical applications. It includes guides, case studies, code examples for model training, optimization, and deployment, as well as insightful articles from industry experts and scholars. Whether you are a beginner or an experienced learner in the field of AI large models, this repository aims to support your learning journey and foster continuous growth and progress.

SystemSculpt AI is a comprehensive AI-powered plugin for Obsidian, integrating advanced AI capabilities into note-taking, task management, knowledge organization, and content creation. It offers modules for brain integration, chat conversations, audio recording and transcription, note templates, and task generation and management. Users can customize settings, utilize AI services like OpenAI and Groq, and access documentation for detailed guidance. The plugin prioritizes data privacy by storing sensitive information locally and offering the option to use local AI models for enhanced privacy.

Midori AI is a cutting-edge initiative dedicated to advancing the field of artificial intelligence through research, development, and community engagement. They focus on creating innovative AI solutions, exploring novel approaches, and empowering users to harness the power of AI. Key areas of focus include cluster-based AI, AI setup assistance, AI development for Discord bots, model serving and hosting, novel AI memory architectures, and Carly - a fully simulated human with advanced AI capabilities. They have also developed the Midori AI Subsystem to streamline AI workloads by providing simplified deployment, standardized configurations, isolation for AI systems, and a growing library of backends and tools.

Awesome AI Tools is a curated list of popular tools and resources for artificial intelligence enthusiasts. It includes a wide range of tools such as machine learning libraries, deep learning frameworks, data visualization tools, and natural language processing resources. Whether you are a beginner or an experienced AI practitioner, this repository aims to provide you with a comprehensive collection of tools to enhance your AI projects and research. Explore the list to discover new tools, stay updated with the latest advancements in AI technology, and find the right resources to support your AI endeavors.

Mo AI Studio is an enterprise-level AI agent running platform that enables the operation of customized intelligent AI agents with system-level capabilities. It supports various IDEs and programming languages, allows modification of multiple files with reasoning, cross-project context modifications, customizable agents, system-level file operations, document writing, question answering, knowledge sharing, and flexible output processors. The platform also offers various setters and a custom component publishing feature. Mo AI Studio is a fusion of artificial intelligence and human creativity, designed to bring unprecedented efficiency and innovation to enterprises.

Alan AI is a comprehensive AI solution that acts as a 'unified brain' for enterprises, interconnecting applications, APIs, and data sources to streamline workflows. It offers tools like Alan AI Studio for designing dialog scenarios, lightweight SDKs for embedding AI Agents, and a backend powered by advanced AI technologies. With Alan AI, users can create conversational experiences with minimal UI changes, benefit from a serverless environment, receive on-the-fly updates, and access dialog testing and analytics tools. The platform supports various frameworks like JavaScript, React, Angular, Vue, Ember, and Electron, and provides example web apps for different platforms. Users can also explore Alan AI SDKs for iOS, Android, Flutter, Ionic, Apache Cordova, and React Native.

Awesome AI is a curated list of artificial intelligence resources including courses, tools, apps, and open-source projects. It covers a wide range of topics such as machine learning, deep learning, natural language processing, robotics, conversational interfaces, data science, and more. The repository serves as a comprehensive guide for individuals interested in exploring the field of artificial intelligence and its applications across various domains.

NotHotDog is an open-source testing framework for evaluating and validating voice and text-based AI agents. It offers a user-friendly interface for creating, managing, and executing tests against AI models. The framework supports WebSocket and REST API, test case management, automated evaluation of responses, and provides a seamless experience for test creation and execution.

Animal-Artificial Intelligence (Animal-AI) is an interdisciplinary research platform designed to understand human, animal, and artificial cognition. It supports AI research to unlock cognitive capabilities and explore the space of possible minds. The open-source project facilitates testing across animals, humans, and AI, providing a comprehensive AI environment with a library of 900 tasks. It offers compatibility with Windows, Linux, and macOS, supporting Python 3.6.x and above. The environment utilizes Unity3D Game Engine, Unity ML-Agents toolkit, and provides interactive elements for AI training scenarios.

Awesome AI Newsletters is a curated list of AI-related newsletters that provide the latest news, trends, tools, and insights in the field of Artificial Intelligence. It includes a variety of newsletters covering general AI news, prompts for marketing and productivity, AI job opportunities, and newsletters tailored for professionals in the AI industry. Whether you are a beginner looking to stay updated on AI advancements or a professional seeking to enhance your knowledge and skills, this repository offers a collection of valuable resources to help you navigate the world of AI.

Wingman-AI is a free and open-source AI coding assistant that brings high-quality AI-assisted coding right to your computer. It offers features such as code completion, interactive chat, and support for multiple AI providers, including Ollama, Hugging Face, and OpenAI. Wingman-AI is designed to enhance your coding workflow by providing real-time assistance and suggestions, making it an ideal tool for developers of all levels.

Awesome Generative AI is a curated list of modern Generative Artificial Intelligence projects and services. Generative AI technology creates original content like images, sounds, and texts using machine learning algorithms trained on large data sets. It can produce unique and realistic outputs such as photorealistic images, digital art, music, and writing. The repo covers a wide range of applications in art, entertainment, marketing, academia, and computer science.

Alan AI SDK for iOS is a powerful tool that allows developers to quickly create AI agents for their iOS apps. With Alan AI Platform, users can easily design, embed, and host conversational experiences in their applications. The platform offers a web-based IDE called Alan AI Studio for creating dialog scenarios, lightweight SDKs for embedding AI agents, and a backend powered by top-notch speech recognition and natural language understanding technologies. Alan AI enables human-like conversations and actions through voice commands, with features like on-the-fly updates, dialog flow testing, and analytics.

Awesome-AI-SEO is a curated list of powerful AI tools and platforms designed to transform your SEO strategy. This repository gathers the most effective tools that leverage machine learning and artificial intelligence to automate and enhance key aspects of search engine optimization. Whether you are an SEO professional, digital marketer, or website owner, these tools can help you optimize your site, improve your search rankings, and increase organic traffic with greater precision and efficiency. The list features AI tools covering on-page and off-page optimization, competitor analysis, rank tracking, and advanced SEO analytics. By utilizing cutting-edge technologies, businesses can stay ahead of the competition by uncovering hidden keyword opportunities, optimizing content for better visibility, and automating time-consuming SEO tasks. With frequent updates, Awesome-AI-SEO is your go-to resource for discovering the latest AI-driven innovations in the SEO space.

Akeru.ai is an open-source AI platform leveraging the power of decentralization. It offers transparent, safe, and highly available AI capabilities. The platform aims to give developers access to open-source and transparent AI resources through its decentralized nature hosted on an edge network. Akeru API introduces features like retrieval, function calling, conversation management, custom instructions, data input optimization, user privacy, testing and iteration, and comprehensive documentation. It is ideal for creating AI agents and enhancing web and mobile applications with advanced AI capabilities. The platform runs on a Bittensor Subnet design that aims to democratize AI technology and promote an equitable AI future. Akeru.ai embraces decentralization challenges to ensure a decentralized and equitable AI ecosystem with security features like watermarking and network pings. The API architecture integrates with technologies like Bun, Redis, and Elysia for a robust, scalable solution.

LSP-AI is an open source language server designed to enhance software engineers' productivity by integrating AI-powered functionality into various text editors. It serves as a backend for completion with large language models and offers features like unified AI capabilities, simplified plugin development, enhanced collaboration, broad compatibility with editors supporting Language Server Protocol, flexible LLM backend support, and commitment to staying updated with the latest advancements in LLM-driven software development. The tool aims to centralize open-source development work, provide a collaborative platform for developers, and offer a future-ready solution for AI-powered assistants in text editors.

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...).

Weave is a toolkit for developing Generative AI applications, built by Weights & Biases. With Weave, you can log and debug language model inputs, outputs, and traces; build rigorous, apples-to-apples evaluations for language model use cases; and organize all the information generated across the LLM workflow, from experimentation to evaluations to production. Weave aims to bring rigor, best-practices, and composability to the inherently experimental process of developing Generative AI software, without introducing cognitive overhead.

LLMStack is a no-code platform for building generative AI agents, workflows, and chatbots. It allows users to connect their own data, internal tools, and GPT-powered models without any coding experience. LLMStack can be deployed to the cloud or on-premise and can be accessed via HTTP API or triggered from Slack or Discord.

The VisionCraft API is a free API for using over 100 different AI models. From images to sound.

Kaito is an operator that automates the AI/ML inference model deployment in a Kubernetes cluster. It manages large model files using container images, avoids tuning deployment parameters to fit GPU hardware by providing preset configurations, auto-provisions GPU nodes based on model requirements, and hosts large model images in the public Microsoft Container Registry (MCR) if the license allows. Using Kaito, the workflow of onboarding large AI inference models in Kubernetes is largely simplified.

PyRIT is an open access automation framework designed to empower security professionals and ML engineers to red team foundation models and their applications. It automates AI Red Teaming tasks to allow operators to focus on more complicated and time-consuming tasks and can also identify security harms such as misuse (e.g., malware generation, jailbreaking), and privacy harms (e.g., identity theft). The goal is to allow researchers to have a baseline of how well their model and entire inference pipeline is doing against different harm categories and to be able to compare that baseline to future iterations of their model. This allows them to have empirical data on how well their model is doing today, and detect any degradation of performance based on future improvements.

Tabby is a self-hosted AI coding assistant, offering an open-source and on-premises alternative to GitHub Copilot. It boasts several key features: * Self-contained, with no need for a DBMS or cloud service. * OpenAPI interface, easy to integrate with existing infrastructure (e.g Cloud IDE). * Supports consumer-grade GPUs.

SPEAR (Simulator for Photorealistic Embodied AI Research) is a powerful tool for training embodied agents. It features 300 unique virtual indoor environments with 2,566 unique rooms and 17,234 unique objects that can be manipulated individually. Each environment is designed by a professional artist and features detailed geometry, photorealistic materials, and a unique floor plan and object layout. SPEAR is implemented as Unreal Engine assets and provides an OpenAI Gym interface for interacting with the environments via Python.

Magick is a groundbreaking visual AIDE (Artificial Intelligence Development Environment) for no-code data pipelines and multimodal agents. Magick can connect to other services and comes with nodes and templates well-suited for intelligent agents, chatbots, complex reasoning systems and realistic characters.