Showing 2801-2820 of 3,069 projects
A repository containing puzzles and challenges for training large language models (LLMs).
A cross-platform library for retrieving detailed information about the CPU hardware on x86, ARM, Linux, Windows, and more.
Open-source implementation of the YOLOv5 object detection model in PyTorch for training custom models.
Federated learning library for distributed AI model training across multiple devices or servers.
Official code and checkpoint release for mobile robot foundation models like GNM, ViNT, and NoMaD.
A Python CLI tool that generates and runs shell commands using LangChain and large language models.
A DynamoDB library that simplifies working with complex hierarchical data and single-table design.
A Jupyter Notebook library for applying data augmentation techniques to improve object detection models.
MeZO: A novel fine-tuning method for language models that requires just forward passes, ideal for vibe coders.
An R project focused on providing high-performance statistical models, data analysis, and visualization tools.
A text-to-video generation model that combines pixel-level and latent diffusion approaches.
An MCP server that enables secure interaction with MySQL databases for AI-powered developer tools.
Minimalistic PyTorch implementation of diffusion models, a powerful class of generative AI models.
A PyTorch-based implementation of the PaddleOCR optical character recognition model, enabling developers to leverage state-of-the-art AI for text detection and recognition.
A curated list of foundation models for vision and language tasks, useful for vibe coders building AI-powered applications.
An AI chatbot for small and medium-sized teams, supporting popular AI models like Deepseek, OpenAI, and Claude.
Parallax is a distributed model serving framework that lets you build your own AI cluster anywhere.
A Ruby implementation of the Model Context Protocol (MCP) for building AI-powered applications.
A multi-agent programmable modeling environment for kids, teachers, and scientists.
A Python library for semi-supervised learning, focused on improving model performance with limited labeled data.
Get weekly updates on trending AI coding tools and projects.