LLM_Notebooks is a repository supporting The Machine Learning Engineer YouTube channel. It contains materials related to various topics such as Generative AI, MLOps, ML projects, Azure Projects, Google VertexAi, ML Tricks, and more. The repository includes notebooks and code in Python and C#, with a focus on Python. The videos on the channel cover a wide range of topics in English and Spanish, organized into playlists based on general themes. The repository links are provided in the video descriptions for easy access. The creator uploads videos regularly and encourages viewers to subscribe, like, and leave constructive comments. The repository serves as a valuable resource for learning and exploring machine learning concepts and tools.

Clipboard Conqueror is a multi-platform omnipresent copilot alternative. Currently requiring a kobold united or openAI compatible back end, this software brings powerful LLM based tools to any text field, the universal copilot you deserve. It simply works anywhere. No need to sign in, no required key. Provided you are using local AI, CC is a data secure alternative integration provided you trust whatever backend you use. *Special thank you to the creators of KoboldAi, KoboldCPP, llamma, openAi, and the communities that made all this possible to figure out.

WritingAIPaper is a comprehensive guide for beginners on crafting AI conference papers. It covers topics like paper structure, core ideas, framework construction, result analysis, and introduction writing. The guide aims to help novices navigate the complexities of academic writing and contribute to the field with clarity and confidence. It also provides tips on readability improvement, logical strength, defensibility, confusion time reduction, and information density increase. The appendix includes sections on AI paper production, a checklist for final hours, common negative review comments, and advice on dealing with paper rejection.

This repository is a comprehensive guide for individuals looking to start and improve their skills in Large Language Models (LLMs) without an advanced background in the field. It provides free resources, online courses, books, articles, and practical tips to become an expert in machine learning. The guide covers topics such as terminology, transformers, prompting, retrieval augmented generation (RAG), and more. It also includes recommendations for podcasts, YouTube videos, and communities to stay updated with the latest news in AI and LLMs.

PearAI is an inventory that curates cutting-edge AI tools in one place, offering a unified interface for seamless tool integration. The repository serves as the conglomeration of all PearAI project repositories, including VSCode fork, AI chat functionalities, landing page, documentation, and server. Contributions are welcome through quests and issue tackling, with the project stack including TypeScript/Electron.js, Next.js/React, Python FastAPI, and Axiom for logging/telemetry.

Commonplace Bot is a modern representation of the commonplace book, leveraging modern technological advancements in computation, data storage, machine learning, and networking. It aims to capture, engage, and share knowledge by providing a platform for users to collect ideas, quotes, and information, organize them efficiently, engage with the data through various strategies and triggers, and transform the data into new mediums for sharing. The tool utilizes embeddings and cached transformations for efficient data storage and retrieval, flips traditional engagement rules by engaging with the user, and enables users to alchemize raw data into new forms like art prompts. Commonplace Bot offers a unique approach to knowledge management and creative expression.

Bagatur chess engine is a powerful Java chess engine that can run on Android devices and desktop computers. It supports the UCI protocol and can be easily integrated into chess programs with user interfaces. The engine is available for download on various platforms and has advanced features like SMP (multicore) support and NNUE evaluation function. Bagatur also includes syzygy endgame tablebases and offers various UCI options for customization. The project started as a personal challenge to create a chess program that could defeat a friend, leading to years of development and improvements.

This repository contains a collection of sample applications and Jupyter Notebooks for hands-on experience with Pinecone vector databases and common AI patterns, tools, and algorithms. It includes production-ready examples for review and support, as well as learning-optimized examples for exploring AI techniques and building applications. Users can contribute, provide feedback, and collaborate to improve the resource.

Obsidian Weaver is a plugin that integrates ChatGPT/GPT-3 into the note-taking workflow of Obsidian. It allows users to easily access AI-generated suggestions and insights within Obsidian, enhancing the writing and brainstorming process. The plugin respects Obsidian's philosophy of storing notes locally, ensuring data security and privacy. Weaver offers features like creating new chat sessions with the AI assistant and receiving instant responses, all within the Obsidian environment. It provides a seamless integration with Obsidian's interface, making the writing process efficient and helping users stay focused. The plugin is constantly being improved with new features and updates to enhance the note-taking experience.

AnkiGPT is a tool that leverages GPT-3.5 or GPT-4 by OpenAI to generate flashcards from lecture slides or text input. Users can easily export the generated flashcards to Anki for effective learning. The tool allows users to edit, delete, and share flashcards, as well as generate mnemonics. AnkiGPT supports nearly all languages and ensures user privacy by not using submitted content for AI training. While powerful, the tool has limitations such as occasional errors in generated flashcards and challenges with mathematical equations. AnkiGPT is designed specifically for Anki flashcard app integration and encourages users to review and verify flashcard information for accuracy.

An artificial intelligence framework entirely written in Java for game development with libGDX. It is a high-performance framework providing common AI techniques used in the game industry, covering movement AI, pathfinding, decision making, and infrastructure. The framework is designed to be used with libGDX but can be used independently. Current features include steering behaviors, formation motion, A* pathfinding, hierarchical pathfinding, behavior trees, state machine, message handling, and scheduling.

The 'curriculum' repository is an open-source content repository by Enki, providing a community-driven curriculum for education. It follows a contributor covenant code of conduct to ensure a safe and engaging learning environment. The content is licensed under Creative Commons, allowing free use for non-commercial purposes with attribution to Enki and the author.

Weeablind is a program that uses modern AI speech synthesis, diarization, language identification, and voice cloning to dub multi-lingual media and anime. It aims to create a pleasant alternative for folks facing accessibility hurdles such as blindness, dyslexia, learning disabilities, or simply those that don't enjoy reading subtitles. The program relies on state-of-the-art technologies such as ffmpeg, pydub, Coqui TTS, speechbrain, and pyannote.audio to analyze and synthesize speech that stays in-line with the source video file. Users have the option of dubbing every subtitle in the video, setting the start and end times, dubbing only foreign-language content, or full-blown multi-speaker dubbing with speaking rate and volume matching.

Web-LLM Assistant is a simple web search assistant that leverages a large language model (LLM) running via Llama.cpp to provide informative and context-aware responses to user queries. It combines the power of LLMs with real-time web searching capabilities, allowing it to access up-to-date information and synthesize comprehensive answers. The tool performs web searches, collects and scrapes information from search results, refines search queries, and provides answers based on the acquired information. Users can interact with the tool by asking questions or requesting web searches, making it a valuable resource for obtaining information beyond the LLM's training data.

Husky is a research-focused programming language designed for next-generation computing. It aims to provide a powerful and ergonomic development experience for various tasks, including system level programming, web/native frontend development, parser/compiler tasks, game development, formal verification, machine learning, and more. With a strong type system and support for human-in-the-loop programming, Husky enables users to tackle complex tasks such as explainable image classification, natural language processing, and reinforcement learning. The language prioritizes debugging, visualization, and human-computer interaction, offering agile compilation and evaluation, multiparadigm support, and a commitment to a good ecosystem.

TypeChat is a library that simplifies the creation of natural language interfaces using types. Traditionally, building natural language interfaces has been challenging, often relying on complex decision trees to determine intent and gather necessary inputs for action. Large language models (LLMs) have simplified this process by allowing us to accept natural language input from users and match it to intent. However, this has introduced new challenges, such as the need to constrain the model's response for safety, structure responses from the model for further processing, and ensure the validity of the model's response. Prompt engineering aims to address these issues, but it comes with a steep learning curve and increased fragility as the prompt grows in size.

LLM_Notebooks is a repository supporting The Machine Learning Engineer YouTube channel. It contains materials related to various topics such as Generative AI, MLOps, ML projects, Azure Projects, Google VertexAi, ML Tricks, and more. The repository includes notebooks and code in Python and C#, with a focus on Python. The videos on the channel cover a wide range of topics in English and Spanish, organized into playlists based on general themes. The repository links are provided in the video descriptions for easy access. The creator uploads videos regularly and encourages viewers to subscribe, like, and leave constructive comments. The repository serves as a valuable resource for learning and exploring machine learning concepts and tools.

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.