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Denoising Diffusion Probabilistic Model
Implementation of Denoising Diffusion Probabilistic Model in Pytorch
Implementation of Denoising Diffusion Probabilistic Model in Pytorch. It is a new approach to generative modeling that may have the potential to rival GANs. It uses denoising score matching to estimate the gradient of the data distribution, followed by Langevin sampling to sample from the true distribution. If you simply want to pass in a folder name and the desired image dimensions, you can use the Trainer class to easily train a model. -
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Helicone
Open source LLM-Observability Platform for Developers
Open source LLM-Observability Platform for Developers. One-line integration for monitoring, metrics, evals, agent tracing, prompt management, playground, etc. Supports OpenAI SDK, Vercel AI SDK, Anthropic SDK, LiteLLM, LLamaIndex, LangChain, and more. -
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Surya
Implementation of the Surya Foundation Model for Heliophysics
Surya is an open‑source, AI‑based foundation model for heliophysics developed collaboratively by NASA (via the IMPACT AI team) and IBM. Named after the Sanskrit word for “sun,” Surya is trained on nine years of high‑resolution solar imagery from NASA’s Solar Dynamics Observatory (SDO). It is designed to forecast solar phenomena—such as flares, solar wind, irradiance, and active region behavior—by predicting future solar images with a sophisticated long–short vision transformer architecture,... -
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AWS MCP Servers
Helping you get the most out of AWS, wherever you use MCP
AWS MCP Servers are a collection of remotely hosted, fully-managed Model Context Protocol (MCP) servers by AWS, providing AI applications with real-time access to AWS documentation, API references, best practices, and infrastructure-management capabilities via natural-language workflows. An MCP Server is a lightweight program that exposes specific capabilities through the standardized Model Context Protocol. Host applications (such as chatbots, IDEs, and other AI tools) have MCP clients that... -
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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MIVisionX
Set of comprehensive computer vision & machine intelligence libraries
MIVisionX toolkit is a set of comprehensive computer vision and machine intelligence libraries, utilities, and applications bundled into a single toolkit. AMD MIVisionX delivers highly optimized open-source implementation of the Khronos OpenVX™ and OpenVX™ Extensions along with Convolution Neural Net Model Compiler & Optimizer supporting ONNX, and Khronos NNEF™ exchange formats. The toolkit allows for rapid prototyping and deployment of optimized computer vision and machine learning... -
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Telegram.Bot
.NET Client for Telegram Bot API
Telegram.Bot is the most popular .NET Client for Telegram Bot API. The Bot API is an HTTP-based interface created for developers keen on building bots for Telegram. Check Bots: An introduction for developers to understand what a Telegram bot is and what it can do. All Bot API methods are already documented by Telegram but this book covers all you need to know to create a chatbot in .NET. There are also many concrete examples written in C#. The guides here can even be useful to bot developers... -
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Claude Relay Service
Claude Code image, a one-stop open source transit service
claude-relay-service is an open-source proxy and relay platform that enables unified access to multiple AI model providers through a single self-hosted gateway. The project is designed to help users centralize subscriptions and API usage for services such as Claude, OpenAI, Gemini, and related tools. It acts as a middleware layer that forwards requests while managing authentication, routing, and cost-sharing scenarios. The system is particularly useful for teams or communities that want to... -
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Open Responses
Specification for multi-provider, interoperable LLM interfaces
...This makes it a powerful option for teams or individuals who want full control over their AI infrastructure, prioritize privacy, or need to standardize inference calls across multiple backends without rewriting their code. -
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Aidea
Flutter-based cross-platform app integrating major AI models
AIdea is a comprehensive Flutter-based cross-platform app integrating major AI models—OpenAI GPT, Chinese models Tongyi Qianwen and Wenxin Yiyan, plus image models like Stable Diffusion for text-to-image, image-to-image, SDXL 1.0, super-resolution, and colorization. It includes a client app, server backend, and Docker deployment scripts for hosted setups. -
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agentmemory
#1 Persistent memory for AI coding agents
agentmemory is a persistent memory server for AI coding agents that captures project context, past decisions, bugs, preferences, and implementation details so users do not have to re-explain the same information in every session. It works across tools such as Claude Code, Cursor, Gemini CLI, Codex CLI, OpenCode, Cline, and any client that supports MCP or REST APIs. The system automatically records what agents do, compresses that activity into searchable memory, and injects relevant context... -
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Evolver
The GEP-Powered Self-Evolution Engine for AI Agents
Evolver is the core engine behind EvoMap and is positioned as a self-evolution system for AI agents rather than a conventional application framework. Its purpose is to turn isolated prompt adjustments into reusable, auditable evolution assets, giving agent teams a more structured way to improve behavior over time. The project uses a protocol-constrained approach centered on concepts such as genes, capsules, and events, which are stored as structured assets and selected through signal... -
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The Pope Bot
Autonomous AI agent that you can configure and build
The Pope Bot is an autonomous AI agent framework that lets users configure and run an AI-powered agent that can perform tasks continuously, day in and day out, by leveraging GitHub Actions, commit history, and secure workflows. It’s designed so that every action taken by the agent is logged as a git commit, giving users complete visibility into what the agent did, why it did it, and when, which makes actions auditable and reversible. The framework treats the repository itself as the agent’s... -
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Open Model Zoo
Pre-trained Deep Learning models and demos
Open Model Zoo is a large repository of high-quality pre-trained deep learning models and demonstration applications designed to work with the OpenVINO™ toolkit, offering a comprehensive starting point for a wide range of AI and computer vision workloads. It includes hundreds of models covering object detection, classification, segmentation, pose estimation, speech recognition, text-to-speech, and more, many of which are already converted into formats optimized for inference on CPUs, GPUs,... -
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nanochat
The best ChatGPT that $100 can buy
nanochat is a from-scratch, end-to-end “mini ChatGPT” that shows the entire path from raw text to a chatty web app in one small, dependency-lean codebase. The repository stitches together every stage of the lifecycle: tokenizer training, pretraining a Transformer on a large web corpus, mid-training on dialogue and multiple-choice tasks, supervised fine-tuning, optional reinforcement learning for alignment, and finally efficient inference with caching. Its north star is approachability and... -
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Tribuo
Tribuo - A Java machine learning library
Tribuo* is a machine learning library written in Java. It provides tools for classification, regression, clustering, model development, and more. It provides a unified interface to many popular third-party ML libraries like xgboost and liblinear. With interfaces to native code, Tribuo also makes it possible to deploy models trained by Python libraries (e.g. scikit-learn, and pytorch) in a Java program. Tribuo is licensed under Apache 2.0. Remove the uncertainty around exactly which artifacts... -
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PML
The easiest way to use deep metric learning in your application
This library contains 9 modules, each of which can be used independently within your existing codebase, or combined together for a complete train/test workflow. To compute the loss in your training loop, pass in the embeddings computed by your model, and the corresponding labels. The embeddings should have size (N, embedding_size), and the labels should have size (N), where N is the batch size. The TripletMarginLoss computes all possible triplets within the batch, based on the labels you... -
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PyG
Graph Neural Network Library for PyTorch
PyG (PyTorch Geometric) is a library built upon PyTorch to easily write and train Graph Neural Networks (GNNs) for a wide range of applications related to structured data. It consists of various methods for deep learning on graphs and other irregular structures, also known as geometric deep learning, from a variety of published papers. In addition, it consists of easy-to-use mini-batch loaders for operating on many small and single giant graphs, multi GPU-support, DataPipe support,... -
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python-small-examples
Focus on creating classic Python small examples and cases
python-small-examples is an open-source educational repository that contains hundreds of concise Python programming examples designed to illustrate practical coding techniques. The project focuses on teaching programming concepts through small, focused scripts that demonstrate common tasks in data processing, visualization, and general programming. Each example highlights a specific function or programming pattern so that learners can quickly understand how to apply Python features in... -
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Nanocoder
A beautiful local-first coding agent running in your terminal
Nanocoder is an open-source, local-first coding assistant that runs in the command line and allows developers to use AI models to assist with programming tasks directly from their terminal environment. The tool is designed as a privacy-focused alternative to proprietary AI coding assistants, allowing users to run local models or connect to external APIs while keeping full control over their data and development workflow. -
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FastAgency
The fastest way to bring multi-agent workflows to production
FastAgency is a framework that simplifies the creation and deployment of AI-driven automation agents. It provides a structured environment for developing AI assistants capable of handling various business and technical tasks. -
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Voqal
Natural speech programming assistant for the software developers
Voqal is a programming assistant built for software developers looking to enhance their productivity with natural speech programming. Using Voqal, you can navigate, write, run, and debug software in JetBrains IDEs using your voice. Write code faster, reduce repetitive strain injuries, and improve focus and productivity. Voqal is promptable and privacy-focused, allowing you to customize your experience and control your data. -
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Genv
GPU environment management and cluster orchestration
Genv is an open-source environment and cluster management system for GPUs. Genv lets you easily control, configure, monitor and enforce the GPU resources that you are using in a GPU machine or cluster. It is intended to ease up the process of GPU allocation for data scientists without code changes. -
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TEN
Open-source framework for conversational voice AI agents
...Using components like graph-based workflow design, drag-and-drop UI (via TMAN Designer), and reusable extensions such as real-time avatars, RAG (Retrieval-Augmented Generation), and image generation, TEN enables highly customizable, scalable agent development with minimal code. -
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OpenSwarm
Claude code for everything except coding
OpenSwarm is an open-source multi-agent system that lets users create full deliverables from a single terminal prompt. Instead of relying on one general-purpose assistant, it coordinates a team of specialized agents through an orchestrator. The included agents can handle research, data analysis, slide decks, documents, images, videos, scheduling, messaging, and other productivity tasks. It is designed for outputs like pitch decks, market research, SEO content, quarterly reports, launch... -
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AI-DLC
AI-Driven Life Cycle (AI-DLC) adaptive workflow steering rules for AI
AI-DLC is an open-source workflow framework from AWS Labs designed to structure software development around AI-assisted engineering processes. The project promotes an “AI-Driven Life Cycle” methodology where coding assistants, IDE agents, and automation systems participate directly in planning, implementation, testing, and operational workflows. Rather than focusing on a single model or IDE, the framework provides reusable rules, templates, and orchestration patterns compatible with tools such as Amazon Q Developer, Claude Code, Cursor, GitHub Copilot, and Cline. ...