LearnPrompt is a permanent, free, open-source AIGC course platform that currently supports various tools like ChatGPT, Agent, Midjourney, Runway, Stable Diffusion, AI digital humans, AI voice & music, and large model fine-tuning. The platform offers features such as multilingual support, comment sections, daily selections, and submissions. Users can explore different modules, including sound cloning, RAG, GPT-SoVits, and OpenAI Sora world model. The platform aims to continuously update and provide tutorials, examples, and knowledge systems related to AI technologies.

This is an offline Japanese translator for RPGMaker games based on Mtool and the Sakura model, capable of providing high-quality offline Japanese translations. It is recommended to use the Sakura-13B-Galgame translation model, and the currently supported versions are Sakura v0.8/v0.9/v0.10pre0.

AI System School is a curated list of research in machine learning systems, focusing on ML/DL infra, LLM infra, domain-specific infra, ML/LLM conferences, and general resources. It provides resources such as data processing, training systems, video systems, autoML systems, and more. The repository aims to help users navigate the landscape of AI systems and machine learning infrastructure, offering insights into conferences, surveys, books, videos, courses, and blogs related to the field.

RealScaler is a Windows app powered by RealESRGAN AI to enhance, upscale, and de-noise photos and videos. It provides an easy-to-use GUI for upscaling images and videos using multiple AI models. The tool supports automatic image tiling and merging to avoid GPU VRAM limitations, resizing images/videos before upscaling, interpolation between original and upscaled content, and compatibility with various image and video formats. RealScaler is written in Python and requires Windows 11/10, at least 8GB RAM, and a Directx12 compatible GPU with 4GB VRAM. Future versions aim to enhance performance, support more GPUs, offer a new GUI with Windows 11 style, include audio for upscaled videos, and provide features like metadata extraction and application from original to upscaled files.

Flare is an open-source AI-powered decentralized social network client for Android/iOS/macOS, consolidating multiple social networks into one platform. It allows cross-posting content, ensures privacy, and plans to implement features like mixed timeline, AI-powered functions, and support for various platforms. The project is in active development and aims to provide a seamless social networking experience for users.

FluidFrames.RIFE is a Windows app powered by RIFE AI to create frame-generated and slowmotion videos. It is written in Python and utilizes external packages such as torch, onnxruntime-directml, customtkinter, OpenCV, moviepy, and Nuitka. The app features an elegant GUI, video frame generation at different speeds, video slow motion, video resizing, multiple GPU support, and compatibility with various video formats. Future versions aim to support different GPU types, enhance the GUI, include audio processing, optimize video processing speed, and introduce new features like saving AI-generated frames and supporting different RIFE AI models.

LLMFarm is an iOS and MacOS app designed to work with large language models (LLM). It allows users to load different LLMs with specific parameters, test the performance of various LLMs on iOS and macOS, and identify the most suitable model for their projects. The tool is based on ggml and llama.cpp by Georgi Gerganov and incorporates sources from rwkv.cpp by saharNooby, Mia by byroneverson, and LlamaChat by alexrozanski. LLMFarm features support for MacOS (13+) and iOS (16+), various inferences and sampling methods, Metal compatibility (not supported on Intel Mac), model setting templates, LoRA adapters support, LoRA finetune support, LoRA export as model support, and more. It also offers a range of inferences including LLaMA, GPTNeoX, Replit, GPT2, Starcoder, RWKV, Falcon, MPT, Bloom, and others. Additionally, it supports multimodal models like LLaVA, Obsidian, and MobileVLM. Users can customize inference options through JSON files and access supported models for download.

QualityScaler is a Windows app powered by AI to enhance, upscale, and de-noise photographs and videos. It provides an easy-to-use GUI for upscaling images and videos using multiple AI models. The tool supports automatic image tiling and merging to avoid GPU VRAM limitations, resizing images/videos before upscaling, and interpolation between the original and upscaled content. QualityScaler is written in Python and utilizes external packages such as torch, onnxruntime-directml, customtkinter, OpenCV, moviepy, and nuitka. It requires Windows 11 or Windows 10, at least 8GB of RAM, and a Directx12 compatible GPU with 4GB VRAM or more. The tool aims to continue improving with upcoming versions by adding new features, enhancing performance, and supporting additional AI architectures.

Painting Droid is an AI-powered cross-platform painting app inspired by MS Paint, expandable with plugins and open. It utilizes various AI models, from paid providers to self-hosted open-source models, as well as some lightweight ones built into the app. Features include regular painting app features, AI-generated content filling and augmentation, filters and effects, image manipulation, plugin support, and cross-platform compatibility.

This repository provides a systematic and comprehensive review of efficient LLMs research. We organize the literature in a taxonomy consisting of three main categories, covering distinct yet interconnected efficient LLMs topics from **model-centric** , **data-centric** , and **framework-centric** perspective, respectively. We hope our survey and this GitHub repository can serve as valuable resources to help researchers and practitioners gain a systematic understanding of the research developments in efficient LLMs and inspire them to contribute to this important and exciting field.

ProChat is a components library focused on quickly building large language model chat interfaces. It empowers developers to create rich, dynamic, and intuitive chat interfaces with features like automatic chat caching, streamlined conversations, message editing tools, auto-rendered Markdown, and programmatic controls. The tool also includes design evolution plans such as customized dialogue rendering, enhanced request parameters, personalized error handling, expanded documentation, and atomic component design.

BMW MD is a simple WhatsApp user BOT created by Ibrahim Tech. It allows users to scan pairing codes or QR codes to connect to WhatsApp and deploy the bot on Heroku. The bot can be used to perform various tasks such as sending messages, receiving messages, and managing contacts. It is released under the MIT License and contributions are welcome.

MLE-Agent is an intelligent companion designed for machine learning engineers and researchers. It features autonomous baseline creation, integration with Arxiv and Papers with Code, smart debugging, file system organization, comprehensive tools integration, and an interactive CLI chat interface for seamless AI engineering and research workflows.

This repository provides a tool for forwarding SMS and call notifications using various notification methods such as Telegram, PushDeer, Bark, DingTalk, Feishu, WeCom, Pushover, email, Gotify, Inotify, and SMTP protocol. It also allows controlling devices via SMS, scheduling base station positioning, querying data usage, reporting device status, power button operations, low power mode, message queue usage for sending notifications without freezing, automatic resend on notification failure, and support for master-slave mode for message forwarding.

This repository is a collection of papers and resources related to recommendation systems, focusing on foundation models, transferable recommender systems, large language models, and multimodal recommender systems. It explores questions such as the necessity of ID embeddings, the shift from matching to generating paradigms, and the future of multimodal recommender systems. The papers cover various aspects of recommendation systems, including pretraining, user representation, dataset benchmarks, and evaluation methods. The repository aims to provide insights and advancements in the field of recommendation systems through literature reviews, surveys, and empirical studies.

Awesome deep logic is a curated list of papers and resources focusing on integrating symbolic logic into deep neural networks. It includes surveys, tutorials, and research papers that explore the intersection of logic and deep learning. The repository aims to provide valuable insights and knowledge on how logic can be used to enhance reasoning, knowledge regularization, weak supervision, and explainability in neural networks.

LearnPrompt is a permanent, free, open-source AIGC course platform that currently supports various tools like ChatGPT, Agent, Midjourney, Runway, Stable Diffusion, AI digital humans, AI voice & music, and large model fine-tuning. The platform offers features such as multilingual support, comment sections, daily selections, and submissions. Users can explore different modules, including sound cloning, RAG, GPT-SoVits, and OpenAI Sora world model. The platform aims to continuously update and provide tutorials, examples, and knowledge systems related to AI technologies.

Leverage AI to generate pull request descriptions based on the diff & commit messages. Install the Chrome Extension to get started. The project uses Node.js and NPM. It provides developer documentation and usage guide. The extension can be installed on Chromium-based browsers by loading the unpacked `dist` directory. The core team includes Brian Douglas, Divyansh Singh, and Anush Shetty. Contributors can open issues and find good first issues in the Discord channel. The project uses @open-sauced/conventional-commit for commit utility and semantic-release for generating changelogs and releases. Join the community in Discord, watch videos on the YouTube Channel, and find resources on the Dev.to org. Licensed under MIT © Open Sauced.

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.