Showing 3021 open source projects for "python windows"

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  • 1
    HunyuanDiT

    HunyuanDiT

    Diffusion Transformer with Fine-Grained Chinese Understanding

    HunyuanDiT is a high-capability text-to-image diffusion transformer with bilingual (Chinese/English) understanding and multi-turn dialogue capability. It trains a diffusion model in latent space using a transformer backbone and integrates a Multimodal Large Language Model (MLLM) to refine captions and support conversational image generation. It supports adapters like ControlNet, IP-Adapter, LoRA, and can run under constrained VRAM via distillation versions. LoRA, ControlNet (pose, depth,...
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  • 2
    NVIDIA Isaac GR00T

    NVIDIA Isaac GR00T

    NVIDIA Isaac GR00T N1.5 is the world's first open foundation model

    NVIDIA Isaac‑GR00T N1.5 is an open-source foundation model engineered for generalized humanoid robot reasoning and manipulation skills. It accepts multimodal inputs—such as language and images—and uses a diffusion transformer architecture built upon vision-language encoders, enabling adaptive robot behaviors across diverse environments. It is designed to be customizable via post-training with real or synthetic data. The vision-language model remains frozen during both pretraining and...
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  • 3
    Kubeflow pipelines

    Kubeflow pipelines

    Machine Learning Pipelines for Kubeflow

    Kubeflow is a machine learning (ML) toolkit that is dedicated to making deployments of ML workflows on Kubernetes simple, portable, and scalable. A pipeline is a description of an ML workflow, including all of the components in the workflow and how they combine in the form of a graph. The pipeline includes the definition of the inputs (parameters) required to run the pipeline and the inputs and outputs of each component. A pipeline component is a self-contained set of user code, packaged as...
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  • 4
    DeepCTR-Torch

    DeepCTR-Torch

    Easy-to-use,Modular and Extendible package of deep-learning models

    DeepCTR-Torch is an easy-to-use, Modular and Extendible package of deep-learning-based CTR models along with lots of core components layers that can be used to build your own custom model easily.It is compatible with PyTorch.You can use any complex model with model.fit() and model.predict(). With the great success of deep learning, DNN-based techniques have been widely used in CTR estimation tasks. The data in the CTR estimation task usually includes high sparse,high cardinality categorical...
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  • 5
    tsai

    tsai

    Time series Timeseries Deep Learning Machine Learning Pytorch fastai

    tsai is an open-source deep learning package built on top of Pytorch & fastai focused on state-of-the-art techniques for time series tasks like classification, regression, forecasting, and imputation. Starting with tsai 0.3.0 tsai will only install hard dependencies. Other soft dependencies (which are only required for selected tasks) will not be installed by default (this is the recommended approach. If you require any of the dependencies that is not installed, tsai will ask you to install...
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  • 6
    Colossal-AI

    Colossal-AI

    Making large AI models cheaper, faster and more accessible

    The Transformer architecture has improved the performance of deep learning models in domains such as Computer Vision and Natural Language Processing. Together with better performance come larger model sizes. This imposes challenges to the memory wall of the current accelerator hardware such as GPU. It is never ideal to train large models such as Vision Transformer, BERT, and GPT on a single GPU or a single machine. There is an urgent demand to train models in a distributed environment....
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  • 7
    IVY

    IVY

    The Unified Machine Learning Framework

    Take any code that you'd like to include. For example, an existing TensorFlow model, and some useful functions from both PyTorch and NumPy libraries. Choose any framework for writing your higher-level pipeline, including data loading, distributed training, analytics, logging, visualization etc. Choose any backend framework which should be used under the hood, for running this entire pipeline. Choose the most appropriate device or combination of devices for your needs. DeepMind releases an...
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  • 8
    TensorFlow Model Garden

    TensorFlow Model Garden

    Models and examples built with TensorFlow

    The TensorFlow Model Garden is a repository with a number of different implementations of state-of-the-art (SOTA) models and modeling solutions for TensorFlow users. We aim to demonstrate the best practices for modeling so that TensorFlow users can take full advantage of TensorFlow for their research and product development. To improve the transparency and reproducibility of our models, training logs on TensorBoard.dev are also provided for models to the extent possible though not all models...
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  • 9
    nano-graphrag

    nano-graphrag

    A simple, easy-to-hack GraphRAG implementation

    nano-graphrag is a lightweight implementation of the GraphRAG approach designed to simplify experimentation with graph-based retrieval-augmented generation systems. GraphRAG expands traditional RAG pipelines by constructing knowledge graphs from documents and using relationships between entities to improve the quality and reasoning of AI responses. The nano-GraphRAG project focuses on reducing complexity by providing a compact and readable codebase that preserves the core functionality of...
    Downloads: 6 This Week
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  • 10
    Continuous Claude v3

    Continuous Claude v3

    Context management for Claude Code. Hooks maintain state via ledgers

    Continuous Claude v3 is a persistent, multi-agent development environment built around the Claude Code CLI that aims to overcome the limitations of standard LLM context windows. Rather than relying on a single session’s context, Continuous Claude uses mechanisms like ledgers, YAML handoffs, and a memory system to preserve and recall state across multiple sessions, ensuring that learned insights and plans are not lost when context compaction occurs. The project orchestrates many specialized...
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  • 11
    WavTokenizer

    WavTokenizer

    SOTA discrete acoustic codec models with 40/75 tokens per second

    WavTokenizer is a state-of-the-art discrete acoustic codec designed specifically for audio language modeling, capable of compressing 24 kHz audio into just 40 or 75 tokens per second while preserving high perceptual quality. It is built to represent speech, music, and general audio with extremely low bitrate, making it ideal as a front-end for large audio language models like GPT-4o and similar architectures. The model uses a single-quantizer design together with temporal compression to...
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  • 12
    MedicalGPT

    MedicalGPT

    MedicalGPT: Training Your Own Medical GPT Model with ChatGPT Training

    MedicalGPT training medical GPT model with ChatGPT training pipeline, implementation of Pretraining, Supervised Finetuning, Reward Modeling and Reinforcement Learning. MedicalGPT trains large medical models, including secondary pre-training, supervised fine-tuning, reward modeling, and reinforcement learning training.
    Downloads: 1 This Week
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  • 13
    Katib

    Katib

    Automated Machine Learning on Kubernetes

    Katib is a Kubernetes-native project for automated machine learning (AutoML). Katib supports Hyperparameter Tuning, Early Stopping and Neural Architecture Search. Katib is a project that is agnostic to machine learning (ML) frameworks. It can tune hyperparameters of applications written in any language of the users’ choice and natively supports many ML frameworks, such as TensorFlow, Apache MXNet, PyTorch, XGBoost, and others. Katib can perform training jobs using any Kubernetes Custom...
    Downloads: 2 This Week
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  • 14
    FlowLens MCP

    FlowLens MCP

    Open-source MCP server that gives your coding agent

    FlowLens MCP Server is an open-source tool designed to give AI-powered coding agents (like Claude Code, Cursor, GitHub Copilot / Codex, and others) full, replayable browser context to dramatically improve debugging, bug reporting, and regression testing for web applications. It works together with a companion browser extension: when a user reproduces a bug or a complicated UI interaction, the extension captures a rich session log, including screen/video recording, network traffic, console...
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  • 15
    AI Marketing Skills

    AI Marketing Skills

    Open-source AI marketing skills for Claude Code

    AI Marketing Skills is a comprehensive open-source framework designed to transform AI agents into fully operational marketing and sales systems by equipping them with structured, reusable “skills” that automate real business workflows. Instead of simple prompts, the project provides complete operational modules that include scripts, scoring systems, and decision-making logic, allowing AI tools like Claude Code to execute complex marketing tasks end-to-end. The system is organized into...
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  • 16
    geo-seo-claude

    geo-seo-claude

    GEO-first SEO skill for Claude Code

    geo-seo-claude is an AI-powered tool designed to automate the creation of geographically optimized SEO content using large language models, helping businesses improve their visibility in local search results. It leverages AI to generate location-specific content tailored to different regions, allowing users to scale SEO efforts across multiple cities or markets without manual content creation. The system focuses on producing structured and keyword-optimized pages that align with search...
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  • 17
    Spring AI Alibaba Examples

    Spring AI Alibaba Examples

    Spring AI Alibaba examples for building and testing AI apps

    Spring AI Alibaba Examples provides a collection of example projects that demonstrate how to use Spring AI and Spring AI Alibaba across different scenarios, from basic setups to more advanced AI applications. It is designed to help developers understand core concepts, explore practical implementations, and follow best practices when building AI-powered systems using the Spring ecosystem. Each module focuses on a specific use case such as chat, image processing, audio handling, graph...
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  • 18
    DeepAudit

    DeepAudit

    AI multi-agent platform for automated code security auditing system

    DeepAudit is an open source code security auditing platform that uses a multi-agent architecture to analyze and identify vulnerabilities in software projects. Instead of relying solely on traditional static analysis, it simulates the reasoning process of security experts through coordinated agents responsible for orchestration, reconnaissance, analysis, and verification. DeepAudit performs deep semantic understanding of code, enabling it to detect complex vulnerabilities that span multiple...
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  • 19
    promptmap2

    promptmap2

    A security scanner for custom LLM applications

    promptmap is an automated security scanner for custom LLM applications that focuses on prompt injection and related attack classes. The project supports both white-box and black-box testing, which means it can either run tests directly against a known model and system prompt configuration or attack an external HTTP endpoint without internal access. Its scanning workflow uses a dual-LLM architecture in which one model acts as the target being tested and another acts as a controller that...
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  • 20
    autoresearch

    autoresearch

    AI agents autonomously run and improve ML experiments overnight

    autoresearch is an experimental framework that enables AI agents to autonomously conduct machine learning research by iteratively modifying and training models. Created by Andrej Karpathy, the project allows an agent to edit the model training code, run short experiments, evaluate results, and repeat the process without human intervention. Each experiment runs for a fixed five-minute training window, enabling rapid iteration and consistent comparison across architectural or hyperparameter...
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  • 21
    Pal

    Pal

    A personal context-agent that learns how you work

    Pal is an open-source AI personal agent built within the Agno ecosystem that functions as an intelligent digital assistant designed to learn from user activity over time. The system acts as an AI-powered “second brain” capable of capturing, organizing, and retrieving personal knowledge such as notes, bookmarks, research findings, people, and meeting information. Instead of acting as a simple chatbot, Pal continuously builds a structured database of a user’s knowledge and context so it can...
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  • 22
    handy-ollama

    handy-ollama

    Implement CPU from scratch and play with large model deployments

    handy-ollama is an open-source educational project designed to help developers and AI enthusiasts learn how to deploy and run large language models locally using the Ollama platform. The repository serves as a structured tutorial that explains how to install, configure, and use Ollama to run modern language models on personal hardware without requiring advanced infrastructure. A key focus of the project is enabling users to run large models even without GPUs by leveraging optimized CPU-based...
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  • 23
    ERNIE

    ERNIE

    The official repository for ERNIE 4.5 and ERNIEKit

    ERNIE is an open-source large-model toolkit and model family from the PaddlePaddle ecosystem that focuses on training, fine-tuning, compression, and practical application of ERNIE large language models. The repository positions ERNIEKit as an industrial-grade development toolkit, emphasizing end-to-end workflows that span high-performance pre-training, supervised fine-tuning, and alignment. It supports both full-parameter training and parameter-efficient approaches so teams can choose...
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  • 24
    BAML

    BAML

    The AI framework that adds the engineering to prompt engineering

    BAML is an open-source framework and domain-specific language designed to bring structured engineering practices to prompt development for large language model applications. Instead of treating prompts as unstructured text, BAML introduces a schema-driven approach where prompts are defined as typed functions with explicit inputs and outputs. This design allows developers to treat language model interactions as predictable software components rather than ad-hoc prompt strings. The framework...
    Downloads: 3 This Week
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  • 25
    LingBot-World

    LingBot-World

    Advancing Open-source World Models

    LingBot-World is an open-source, high-fidelity world simulator designed to advance the state of world models through video generation. Built on top of Wan2.2, it enables realistic, dynamic environment simulation across diverse styles, including real-world, scientific, and stylized domains. LingBot-World supports long-term temporal consistency, maintaining coherent scenes and interactions over minute-level horizons. With real-time interactivity and sub-second latency at 16 FPS, it is...
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