Showing 6999 open source projects for "gnu/linux"

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  • 1
    Kubeflow Training Operator

    Kubeflow Training Operator

    Distributed ML Training and Fine-Tuning on Kubernetes

    Kubeflow Training Operator is a Kubernetes-native project for fine-tuning and scalable distributed training of machine learning (ML) models created with various ML frameworks such as PyTorch, TensorFlow, XGBoost, MPI, Paddle, and others.
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  • 2
    pmdarima

    pmdarima

    Statistical library designed to fill the void in Python's time series

    A statistical library designed to fill the void in Python's time series analysis capabilities, including the equivalent of R's auto.arima function.
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  • 3
    NGBoost

    NGBoost

    Natural Gradient Boosting for Probabilistic Prediction

    ngboost is a Python library that implements Natural Gradient Boosting, as described in "NGBoost: Natural Gradient Boosting for Probabilistic Prediction". It is built on top of Scikit-Learn and is designed to be scalable and modular with respect to the choice of proper scoring rule, distribution, and base learner. A didactic introduction to the methodology underlying NGBoost is available in this slide deck.
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  • 4
    MLJ.jl

    MLJ.jl

    A Julia machine learning framework

    MLJ (Machine Learning in Julia) is a toolbox written in Julia providing a common interface and meta-algorithms for selecting, tuning, evaluating, composing, and comparing about 200 machine learning models written in Julia and other languages. The functionality of MLJ is distributed over several repositories illustrated in the dependency chart below. These repositories live at the JuliaAI umbrella organization.
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  • 5
    Scanpy

    Scanpy

    Single-cell analysis in Python

    Scanpy is a scalable toolkit for analyzing single-cell gene expression data built jointly with anndata. It includes preprocessing, visualization, clustering, trajectory inference and differential expression testing. The Python-based implementation efficiently deals with datasets of more than one million cells.
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  • 6
    Gp.nvim

    Gp.nvim

    Gp.nvim (GPT prompt) Neovim AI plugin

    Gp.nvim (GPT prompt) Neovim AI plugin: ChatGPT sessions & Instructable text/code operations & Speech to text [OpenAI, Ollama, Anthropic, ..] The goal is to extend Neovim with the power of GPT models in a simple unobtrusive extensible way. Trying to keep things as native as possible - reusing and integrating well with the natural features of (Neo)vim.
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  • 7
    Alibi Detect

    Alibi Detect

    Algorithms for outlier, adversarial and drift detection

    Alibi Detect is an open source Python library focused on outlier, adversarial and drift detection. The package aims to cover both online and offline detectors for tabular data, text, images and time series. Both TensorFlow and PyTorch backends are supported for drift detection.
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  • 8
    DataDrivenDiffEq.jl

    DataDrivenDiffEq.jl

    Data driven modeling and automated discovery of dynamical systems

    DataDrivenDiffEq.jl is a package for finding systems of equations automatically from a dataset. The methods in this package take in data and return the model which generated the data. A known model is not required as input. These methods can estimate equation-free and equation-based models for discrete, continuous differential equations or direct mappings.
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  • 9
    LLaMA Efficient Tuning

    LLaMA Efficient Tuning

    Easy-to-use LLM fine-tuning framework (LLaMA-2, BLOOM, Falcon

    Easy-to-use LLM fine-tuning framework (LLaMA-2, BLOOM, Falcon, Baichuan, Qwen, ChatGLM2)
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  • 10
    Fulling

    Fulling

    Full-stack Engineer Agent. Built with Next.js, Claude, shadcn/ui

    ...The platform provides a sandboxed workspace where developers can build complete applications with the help of an integrated AI coding agent. Instead of manually configuring development environments, the system automatically provisions the required infrastructure including a Linux environment, database services, and development tools. It integrates an AI pair programmer that can generate code, implement features, and assist with debugging tasks through natural language instructions. The environment also includes web-based terminals, file management tools, and version control capabilities to support collaborative software development workflows. ...
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  • 11
    Transformers.jl

    Transformers.jl

    Julia Implementation of Transformer models

    Transformers.jl is a Julia library that implements Transformer models for natural language processing tasks. Inspired by architectures like BERT, GPT, and T5, the library offers a modular and flexible interface for building, training, and using transformer-based deep learning models. It supports training from scratch and fine-tuning pretrained models, and integrates with Flux.jl for automatic differentiation and optimization.
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  • 12
    Appfl

    Appfl

    Advanced Privacy-Preserving Federated Learning framework

    APPFL (Advanced Privacy-Preserving Federated Learning) is a Python framework enabling researchers to easily build and benchmark privacy-aware federated learning solutions. It supports flexible algorithm development, differential privacy, secure communications, and runs efficiently on HPC and multi-GPU setups.
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  • 13
    Substra

    Substra

    Low-level Python library used to interact with a Substra network

    An open-source framework supporting privacy-preserving, traceable federated learning and machine learning orchestration. Offers a Python SDK, high-level FL library (SubstraFL), and web UI to define datasets, models, tasks, and orchestrate secure, auditable collaborations.
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  • 14
    Resume-Matcher

    Resume-Matcher

    Improve your resumes with Resume Matcher

    Resume-Matcher is a command-line application that compares resumes against job descriptions using natural language processing. It provides a compatibility score based on keyword relevance and highlights areas where the resume aligns—or doesn't—with the target role. Designed for job seekers and HR professionals, it helps improve resume tailoring and streamlines candidate screening.
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  • 15
    Techniques

    Techniques

    Techniques for deep learning with satellite & aerial imagery

    This repository is a comprehensive, curated collection of deep learning techniques and best practices specifically applied to satellite and aerial imagery. It covers everything from preprocessing and annotation to model architectures and open datasets. The guide includes code snippets, links to research papers, and hands-on tools, making it valuable for researchers, engineers, and enthusiasts working in remote sensing and geospatial AI.
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  • 16
    Instructor Python

    Instructor Python

    Structured outputs for llms

    Instructor is a Python library that bridges OpenAI responses with structured data validation using Pydantic models. It lets developers specify expected output schemas and ensures that the responses from OpenAI APIs are automatically parsed and validated against those models. This makes integrating LLMs into structured workflows safer and more predictable, especially in production applications.
    Downloads: 0 This Week
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  • 17
    Eigenfocus

    Eigenfocus

    Self-Hosted - Project Management, Planning and Time Tracker

    Eigenfocus is an AI-powered personal knowledge management system that uses embeddings and semantic search to help users organize and retrieve ideas across documents. Designed for researchers and creatives, it enables deep linking between notes and supports querying based on meaning rather than keywords.
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  • 18
    Model Explorer

    Model Explorer

    A modern model graph visualizer and debugger

    Model Explorer is a visual tool for exploring, debugging, and optimizing ML models deployed on edge devices. Developed by Google AI Edge, it offers a browser-based interface to inspect layer-wise performance, memory usage, and inference timing of TensorFlow Lite and other supported models. It’s a powerful utility for developers optimizing models for constrained environments.
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  • 19
    pgai

    pgai

    A suite of tools to develop RAG, semantic search, and other AI apps

    pgai is a suite of PostgreSQL extensions developed by Timescale to empower developers in building AI applications directly within their databases. It integrates tools for vector storage, advanced indexing, and AI model interactions, facilitating the development of applications like semantic search and Retrieval-Augmented Generation (RAG) without leaving the SQL environment.
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  • 20
    Cybergod

    Cybergod

    A program that can do anything to earn money without human operators

    AGI Computer Control is an experimental autonomous software system designed to operate independently and generate income without human intervention. It aims to simulate artificial general intelligence (AGI) by leveraging evolutionary algorithms, deep active inference, and other advanced AI techniques. The project explores the boundaries of machine autonomy and self-directed behavior in computational environments.
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  • 21
    Quarkus MCP Server

    Quarkus MCP Server

    This extension enables developers to implement the MCP server

    The quarkus-mcp-server is a Quarkus extension that enables developers to implement Model Context Protocol (MCP) server features easily. It provides both declarative and programmatic APIs, simplifying the process of integrating MCP functionalities into Quarkus applications. This extension is part of the Quarkiverse, a hub for Quarkus extensions contributed by the community. ​
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  • 22
    Replicate Flux MCP

    Replicate Flux MCP

    MCP for Replicate Flux Model

    The Replicate Flux MCP is an advanced Model Context Protocol server that empowers AI assistants to generate high-quality images and vector graphics. It leverages Black Forest Labs' Flux Schnell model for raster images and Recraft's V3 SVG model for vector graphics via the Replicate API. ​
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  • 23
    SonarQube MCP Server

    SonarQube MCP Server

    Model Context Protocol (MCP) server for SonarQube

    The SonarQube MCP Server is a Rust implementation that integrates SonarQube's code quality analysis with AI assistants through the Model Context Protocol. It provides access to code metrics, issues, quality gate statuses, and project quality analysis. ​
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  • 24
    DeepSource MCP Server

    DeepSource MCP Server

    Model Context Protocol (MCP) server for DeepSource

    The DeepSource MCP Server enables AI assistants to interact with DeepSource's code quality analysis capabilities through the Model Context Protocol. It allows retrieval of code metrics, access to issues, quality status checks, and analysis of project quality over time. ​
    Downloads: 0 This Week
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  • 25
    MCP Package Version

    MCP Package Version

    An MCP server that provides LLMs with the latest stable package

    The Package Version MCP Server provides tools for checking the latest stable package versions from multiple package registries, including npm, PyPI, Maven Central, Go Proxy, Swift Packages, AWS Bedrock, Docker Hub, GitHub Container Registry, and GitHub Actions. ​
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