FluxAIGridComparisons is a repository containing a collection of different image grids generated using Flux. These grids showcase various attributes such as hairstyles, clothing, nationalities, and ages. The repository serves as a visual comparison tool for exploring different characteristics within images.

Krita-AI-Diffusion is a plugin for Krita that allows users to generate images from within the program. It offers a variety of features, including inpainting, outpainting, generating images from scratch, refining existing content, live painting, and control over image creation. The plugin is designed to fit into an interactive workflow where AI generation is used as just another tool while painting. It is meant to synergize with traditional tools and the layer stack.

Large Language Models (LLM) are language models built by deep neural networks containing hundreds of billions of weights, trained on a large amount of unlabeled text using self-supervised learning methods. Since 2018, companies and research institutions including Google, OpenAI, Meta, Baidu, and Huawei have released various models such as BERT, GPT, etc., which have performed well in almost all natural language processing tasks. Starting in 2021, large models have shown explosive growth, especially after the release of ChatGPT in November 2022, attracting worldwide attention. Users can interact with systems using natural language to achieve various tasks from understanding to generation, including question answering, classification, summarization, translation, and chat. Large language models demonstrate powerful knowledge of the world and understanding of language. This repository introduces the basic theory of large language models including language models, distributed model training, and reinforcement learning, and uses the Deepspeed-Chat framework as an example to introduce the implementation of large language models and ChatGPT-like systems.

This repository contains a collection of resources for learning about and using Large Language Models (LLMs). The resources include tutorials, code examples, and links to additional resources. LLMs are a type of artificial intelligence that can understand and generate human-like text. They have a wide range of potential applications, including natural language processing, machine translation, and chatbot development.

Enterprise h2oGPTe - GenAI RAG is a repository containing code examples, notebooks, and benchmarks for the enterprise version of h2oGPTe, a powerful AI tool for generating text based on the RAG (Retrieval-Augmented Generation) architecture. The repository provides resources for leveraging h2oGPTe in enterprise settings, including implementation guides, performance evaluations, and best practices. Users can explore various applications of h2oGPTe in natural language processing tasks, such as text generation, content creation, and conversational AI.

This repository provides baselines for various competitions, a few top solutions for some competitions, and independent deep learning projects. Baselines serve as entry guides for competitions, suitable for beginners to make their first submission. Top solutions are more complex and refined versions of baselines, with limited quantity but enhanced quality. The repository is maintained by a single author, yunsuxiaozi, offering code improvements and annotations for better understanding. Users can support the repository by learning from it and providing feedback.

This repository contains material related to the new book _Synthetic Data and Generative AI_ by the author, including code for NoGAN, DeepResampling, and NoGAN_Hellinger. NoGAN is a tabular data synthesizer that outperforms GenAI methods in terms of speed and results, utilizing state-of-the-art quality metrics. DeepResampling is a fast NoGAN based on resampling and Bayesian Models with hyperparameter auto-tuning. NoGAN_Hellinger combines NoGAN and DeepResampling with the Hellinger model evaluation metric.

This repository showcases the author's experiments with Large Language Models (LLMs) for text generation tasks. It includes dataset preparation, preprocessing, model fine-tuning using libraries such as Axolotl and HuggingFace, and model evaluation.

This repository contains a collection of AI projects implemented in Python, primarily in Jupyter notebooks. The projects cover various aspects of artificial intelligence, including machine learning, deep learning, natural language processing, computer vision, and more. Each project is designed to showcase different AI techniques and algorithms, providing a hands-on learning experience for users interested in exploring the field of artificial intelligence.

Glisten-ai Tutorial Course is the final code for a YouTube tutorial course demonstrating the creation of a dark Next.js, Prismic, Tailwind, TypeScript, and GSAP website. The repository contains the code used in the tutorial, providing a practical example for building websites using these technologies.

The ByteIR Project is a ByteDance model compilation solution. ByteIR includes compiler, runtime, and frontends, and provides an end-to-end model compilation solution. Although all ByteIR components (compiler/runtime/frontends) are together to provide an end-to-end solution, and all under the same umbrella of this repository, each component technically can perform independently. The name, ByteIR, comes from a legacy purpose internally. The ByteIR project is NOT an IR spec definition project. Instead, in most scenarios, ByteIR directly uses several upstream MLIR dialects and Google Mhlo. Most of ByteIR compiler passes are compatible with the selected upstream MLIR dialects and Google Mhlo.

This repository is a collection of LLM notebooks with tutorials and projects. It covers topics such as Transformers tutorials, LLM notebooks and their applications, tools and technologies of GenAI, courses in GenAI, and Generative AI blogs/articles. Contributions are welcome.

SciML.ai is an open source software organization dedicated to unifying packages for scientific machine learning. It focuses on developing modular scientific simulation support software, including differential equation solvers, inverse problems methodologies, and automated model discovery. The organization aims to provide a diverse set of tools with a common interface, creating a modular, easily-extendable, and highly performant ecosystem for scientific simulations. The website serves as a platform to showcase SciML organization's packages and share news within the ecosystem. Pull requests are encouraged for contributions.

A drill of scientific methods, processes, algorithms, and systems to build stories & models. An in-depth learning resource for humans. This repository is designed for individuals aiming to excel in the field of Data and AI, providing video sessions and text content for learning. It caters to those in leadership positions, professionals, and students, emphasizing the need for dedicated effort to achieve excellence in the tech field. The content covers various topics with a focus on practical application.

GenAiGuidebook is a comprehensive resource for individuals looking to begin their journey in GenAI. It serves as a detailed guide providing insights, tips, and information on various aspects of GenAI technology. The guidebook covers a wide range of topics, including introductory concepts, practical applications, and best practices in the field of GenAI. Whether you are a beginner or an experienced professional, this resource aims to enhance your understanding and proficiency in GenAI.

AimRT is a basic runtime framework for modern robotics, developed in modern C++ with lightweight and easy deployment. It integrates research and development for robot applications in various deployment scenarios, providing debugging tools and observability support. AimRT offers a plug-in development interface compatible with ROS2, HTTP, Grpc, and other ecosystems for progressive system upgrades.

FluxAIGridComparisons is a repository containing a collection of different image grids generated using Flux. These grids showcase various attributes such as hairstyles, clothing, nationalities, and ages. The repository serves as a visual comparison tool for exploring different characteristics within images.

Awesome AI is a repository that collects and shares resources in the fields of large language models (LLM), AI-assisted programming, AI drawing, and more. It explores the application and development of generative artificial intelligence. The repository provides information on various AI tools, models, and platforms, along with tutorials and web products related to AI technologies.

sdkit (stable diffusion kit) is an easy-to-use library for utilizing Stable Diffusion in AI Art projects. It includes features like ControlNets, LoRAs, Textual Inversion Embeddings, GFPGAN, CodeFormer for face restoration, RealESRGAN for upscaling, k-samplers, support for custom VAEs, NSFW filter, model-downloader, parallel GPU support, and more. It offers a model database, auto-scanning for malicious models, and various optimizations. The API consists of modules for loading models, generating images, filters, model merging, and utilities, all managed through the sdkit.Context object.

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.

FluxAIGridComparisons is a repository containing a collection of different image grids generated using Flux. These grids showcase various attributes such as hairstyles, clothing, nationalities, and ages. The repository serves as a visual comparison tool for exploring different characteristics within images.

FuseAI is a repository that focuses on knowledge fusion of large language models. It includes FuseChat, a state-of-the-art 7B LLM on MT-Bench, and FuseLLM, which surpasses Llama-2-7B by fusing three open-source foundation LLMs. The repository provides tech reports, releases, and datasets for FuseChat and FuseLLM, showcasing their performance and advancements in the field of chat models and large language models.

Prajna is an open-source programming language specifically developed for building more modular, automated, and intelligent artificial intelligence infrastructure. It aims to cater to various stages of AI research, training, and deployment by providing easy access to CPU, GPU, and various TPUs for AI computing. Prajna features just-in-time compilation, GPU/heterogeneous programming support, tensor computing, syntax improvements, and user-friendly interactions through main functions, Repl, and Jupyter, making it suitable for algorithm development and deployment in various scenarios.

LangChain-Udemy-Course is a comprehensive course directory focusing on LangChain, a framework for generative AI applications. The course covers various aspects such as OpenAI API usage, prompt templates, Chains exploration, callback functions, memory techniques, RAG implementation, autonomous agents, hybrid search, LangSmith utilization, microservice architecture, and LangChain Expression Language. Learners gain theoretical knowledge and practical insights to understand and apply LangChain effectively in generative AI scenarios.

A curated list of open-ended learning AI resources focusing on algorithms that invent new and complex tasks endlessly, inspired by human advancements. The repository includes papers, safety considerations, surveys, perspectives, and blog posts related to open-ended AI research.