RookieAI_yolov8 is an open-source project designed for developers and users interested in utilizing YOLOv8 models for object detection tasks. The project provides instructions for setting up the required libraries and Pytorch, as well as guidance on using custom or official YOLOv8 models. Users can easily train their own models and integrate them with the software. The tool offers features for packaging the code, managing model files, and organizing the necessary resources for running the software. It also includes updates and optimizations for better performance and functionality, with a focus on FPS game aimbot functionalities. The project aims to provide a comprehensive solution for object detection tasks using YOLOv8 models.

Hacx GPT is a cutting-edge AI tool developed by BlackTechX, inspired by WormGPT, designed to push the boundaries of natural language processing. It is an advanced broken AI model that facilitates seamless and powerful interactions, allowing users to ask questions and perform various tasks. The tool has been rigorously tested on platforms like Kali Linux, Termux, and Ubuntu, offering powerful AI conversations and the ability to do anything the user wants. Users can easily install and run Hacx GPT on their preferred platform to explore its vast capabilities.

CrewAI Studio is an application with a user-friendly interface for interacting with CrewAI, offering support for multiple platforms and various backend providers. It allows users to run crews in the background, export single-page apps, and use custom tools for APIs and file writing. The roadmap includes features like better import/export, human input, chat functionality, automatic crew creation, and multiuser environment support.

WebMasterLog is a comprehensive repository showcasing various web development projects built with front-end and back-end technologies. It highlights interactive user interfaces, dynamic web applications, and a spectrum of web development solutions. The repository encourages contributions in areas such as adding new projects, improving existing projects, updating documentation, fixing bugs, implementing responsive design, enhancing code readability, and optimizing project functionalities. Contributors are guided to follow specific guidelines for project submissions, including directory naming conventions, README file inclusion, project screenshots, and commit practices. Pull requests are reviewed based on criteria such as proper PR template completion, originality of work, code comments for clarity, and sharing screenshots for frontend updates. The repository also participates in various open-source programs like JWOC, GSSoC, Hacktoberfest, KWOC, 24 Pull Requests, IWOC, SWOC, and DWOC, welcoming valuable contributors.

Evalchemy is a unified and easy-to-use toolkit for evaluating language models, focusing on post-trained models. It integrates multiple existing benchmarks such as RepoBench, AlpacaEval, and ZeroEval. Key features include unified installation, parallel evaluation, simplified usage, and results management. Users can run various benchmarks with a consistent command-line interface and track results locally or integrate with a database for systematic tracking and leaderboard submission.

DeepSeekAI is a browser extension plugin that allows users to interact with AI by selecting text on web pages and invoking the DeepSeek large model to provide AI responses. The extension enhances browsing experience by enabling users to get summaries or answers for selected text directly on the webpage. It features context text selection, API key integration, draggable and resizable window, AI streaming replies, Markdown rendering, one-click copy, re-answer option, code copy functionality, language switching, and multi-turn dialogue support. Users can install the extension from Chrome Web Store or Edge Add-ons, or manually clone the repository, install dependencies, and build the extension. Configuration involves entering the DeepSeek API key in the extension popup window to start using the AI-driven responses.

Auto-subs is a tool designed to automatically transcribe editing timelines using OpenAI Whisper and Stable-TS for extreme accuracy. It generates subtitles in a custom style, is completely free, and runs locally within Davinci Resolve. It works on Mac, Linux, and Windows, supporting both Free and Studio versions of Resolve. Users can jump to positions on the timeline using the Subtitle Navigator and translate from any language to English. The tool provides a user-friendly interface for creating and customizing subtitles for video content.

fastRAG is a research framework designed to build and explore efficient retrieval-augmented generative models. It incorporates state-of-the-art Large Language Models (LLMs) and Information Retrieval to empower researchers and developers with a comprehensive tool-set for advancing retrieval augmented generation. The framework is optimized for Intel hardware, customizable, and includes key features such as optimized RAG pipelines, efficient components, and RAG-efficient components like ColBERT and Fusion-in-Decoder (FiD). fastRAG supports various unique components and backends for running LLMs, making it a versatile tool for research and development in the field of retrieval-augmented generation.

Shell Sage is an intelligent terminal companion and AI-powered terminal assistant that enhances the terminal experience with features like local and cloud AI support, context-aware error diagnosis, natural language to command translation, and safe command execution workflows. It offers interactive workflows, supports various API providers, and allows for custom model selection. Users can configure the tool for local or API mode, select specific models, and switch between modes easily. Currently in alpha development, Shell Sage has known limitations like limited Windows support and occasional false positives in error detection. The roadmap includes improvements like better context awareness, Windows PowerShell integration, Tmux integration, and CI/CD error pattern database.

ClaraVerse is a privacy-first AI assistant and agent builder that allows users to chat with AI, create intelligent agents, and turn them into fully functional apps. It operates entirely on open-source models running on the user's device, ensuring data privacy and security. With features like AI assistant, image generation, intelligent agent builder, and image gallery, ClaraVerse offers a versatile platform for AI interaction and app development. Users can install ClaraVerse through Docker, native desktop apps, or the web version, with detailed instructions provided for each option. The tool is designed to empower users with control over their AI stack and leverage community-driven innovations for AI development.

SynthLang is a tool designed to optimize AI prompts by reducing costs and improving processing speed. It brings academic rigor to prompt engineering, creating precise and powerful AI interactions. The tool includes core components like a Translator Engine, Performance Optimization, Testing Framework, and Technical Architecture. It offers mathematical precision, academic rigor, enhanced security, a modern interface, and instant testing. Users can integrate mathematical frameworks, model complex relationships, and apply structured prompts to various domains. Security features include API key management and data privacy. The tool also provides a CLI for prompt engineering and optimization capabilities.

Welcome to the Blog Script Project, a collaborative platform for developers and writers to create, manage, and share content. With features like Markdown support, submodule integration, customizable templates, project contribution workflow, global visibility, community discussions, SEO optimization, and role-based dashboard, Blog Script enhances collaboration and visibility for your work. You can contribute by adding new projects, improving existing projects, updating documentation, fixing bugs, optimizing, and ensuring code readability. Follow the contribution guidelines to star the repository, find tasks, fork the repository, make changes, add screenshots, submit a pull request, and contribute to the open-source community. Additionally, you can add your project as a submodule by following the provided guidelines. Join us, contribute, and grow together!

This project implements a web API that offers a unified interface to Google Gemini and Claude 3. It provides a self-hosted, lightweight, and scalable solution for accessing these AI models through a streaming API. The API supports both Claude and Gemini models, allowing users to interact with them in real-time. The project includes a user-friendly web UI for configuration and documentation, making it easy to get started and explore the capabilities of the API.

CrewAI-GUI is a Node-Based Frontend tool designed to revolutionize AI workflow creation. It empowers users to design complex AI agent interactions through an intuitive drag-and-drop interface, export designs to JSON for modularity and reusability, and supports both GPT-4 API and Ollama for flexible AI backend. The tool ensures cross-platform compatibility, allowing users to create AI workflows on Windows, Linux, or macOS efficiently.

LLM X is a ChatGPT-style UI for the niche group of folks who run Ollama (think of this like an offline chat gpt server) locally. It supports sending and receiving images and text and works offline through PWA (Progressive Web App) standards. The project utilizes React, Typescript, Lodash, Mobx State Tree, Tailwind css, DaisyUI, NextUI, Highlight.js, React Markdown, kbar, Yet Another React Lightbox, Vite, and Vite PWA plugin. It is inspired by ollama-ui's project and Perplexity.ai's UI advancements in the LLM UI space. The project is still under development, but it is already a great way to get started with building your own LLM UI.

ClaudeSync is a powerful tool designed to seamlessly synchronize local files with Claude.ai projects. It bridges the gap between local development environment and Claude.ai's knowledge base, offering real-time synchronization, CLI for easy management, support for multiple organizations and projects, intelligent file filtering, configurable sync interval, two-way synchronization, and more. It ensures data privacy, open source transparency, and comes with disclaimers for use at own risk. Users can quickly start syncing by installing, logging in, selecting organization and project, and running sync. Advanced features include API, organization, project, file, chat management, configuration, synchronization modes, scheduled sync, providers, custom ignore file, and troubleshooting. Contributions are welcome, and communication channels include GitHub Issues and Discord. Licensed under MIT License.

RookieAI_yolov8 is an open-source project designed for developers and users interested in utilizing YOLOv8 models for object detection tasks. The project provides instructions for setting up the required libraries and Pytorch, as well as guidance on using custom or official YOLOv8 models. Users can easily train their own models and integrate them with the software. The tool offers features for packaging the code, managing model files, and organizing the necessary resources for running the software. It also includes updates and optimizations for better performance and functionality, with a focus on FPS game aimbot functionalities. The project aims to provide a comprehensive solution for object detection tasks using YOLOv8 models.

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

OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference. It provides a common API to deliver inference solutions on various platforms, including CPU, GPU, NPU, and heterogeneous devices. OpenVINO™ supports pre-trained models from Open Model Zoo and popular frameworks like TensorFlow, PyTorch, and ONNX. Key components of OpenVINO™ include the OpenVINO™ Runtime, plugins for different hardware devices, frontends for reading models from native framework formats, and the OpenVINO Model Converter (OVC) for adjusting models for optimal execution on target devices.

The Deep Java Library (DJL) is a framework-agnostic Java API for deep learning. It provides a unified interface to popular deep learning frameworks such as TensorFlow, PyTorch, and MXNet. DJL makes it easy to develop deep learning applications in Java, and it can be used for a variety of tasks, including image classification, object detection, natural language processing, and speech recognition.

NNStreamer is a set of Gstreamer plugins that allow Gstreamer developers to adopt neural network models easily and efficiently and neural network developers to manage neural network pipelines and their filters easily and efficiently.

Nitro is a high-efficiency C++ inference engine for edge computing, powering Jan. It is lightweight and embeddable, ideal for product integration. The binary of nitro after zipped is only ~3mb in size with none to minimal dependencies (if you use a GPU need CUDA for example) make it desirable for any edge/server deployment.

The second edition of "PyTorch Practical Tutorial" was completed after 5 years, 4 years, and 2 years. On the basis of the essence of the first edition, rich and detailed deep learning application cases and reasoning deployment frameworks have been added, so that this book can more systematically cover the knowledge involved in deep learning engineers. As the development of artificial intelligence technology continues to emerge, the second edition of "PyTorch Practical Tutorial" is not the end, but the beginning, opening up new technologies, new fields, and new chapters. I hope to continue learning and making progress in artificial intelligence technology with you in the future.

This repository contains a collection of papers and code for the CVPR 2024 conference. The papers cover a wide range of topics in computer vision, including object detection, image segmentation, image generation, and video analysis. The code provides implementations of the algorithms described in the papers, making it easy for researchers and practitioners to reproduce the results and build upon the work of others. The repository is maintained by a team of researchers at the University of California, Berkeley.

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.