Showing 7001 open source projects for "gnu/linux"

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  • 1
    flair

    flair

    A very simple framework for state-of-the-art NLP

    A very simple framework for state-of-the-art NLP. Developed by Humboldt University of Berlin and friends. A powerful NLP library. Flair allows you to apply our state-of-the-art natural language processing (NLP) models to your text, such as named entity recognition (NER), sentiment analysis, part-of-speech tagging (PoS), special support for biomedical texts, sense disambiguation and classification, with support for a rapidly growing number of languages. A text embedding library. Flair has...
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  • 2
    Code Review GPT

    Code Review GPT

    Your personal code reviewer powered by LLMs

    Code Review GPT uses Large Language Models to review code in your CI/CD pipeline. It helps streamline the code review process by providing feedback on code that may have issues or areas for improvement. Code Review GPT is in alpha and should be used for fun only. It may provide useful feedback but please check any suggestions thoroughly.
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  • 3
    Guardrails

    Guardrails

    Adding guardrails to large language models

    Guardrails is a Python package that lets a user add structure, type and quality guarantees to the outputs of large language models (LLMs). At the heart of Guardrails is the rail spec. rail is intended to be a language-agnostic, human-readable format for specifying structure and type information, validators and corrective actions over LLM outputs. We create a RAIL spec to describe the expected structure and types of the LLM output, the quality criteria for the output to be considered valid,...
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  • 4
    Scikit-LLM

    Scikit-LLM

    Seamlessly integrate LLMs into scikit-learn

    Seamlessly integrate powerful language models like ChatGPT into sci-kit-learn for enhanced text analysis tasks. At the moment the majority of the Scikit-LLM estimators are only compatible with some of the OpenAI models. Hence, a user-provided OpenAI API key is required. Additionally, Scikit-LLM will ensure that the obtained response contains a valid label. If this is not the case, a label will be selected randomly (label probabilities are proportional to label occurrences in the training...
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  • Stop Storing Third-Party Tokens in Your Database Icon
    Stop Storing Third-Party Tokens in Your Database

    Auth0 Token Vault handles secure token storage, exchange, and refresh for external providers so you don't have to build it yourself.

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  • 5
    bbox-visualizer

    bbox-visualizer

    Make drawing and labeling bounding boxes easy as cake

    Make drawing and labeling bounding boxes easy as cake. This package helps users draw bounding boxes around objects, without doing the clumsy math that you'd need to do for positioning the labels. It also has a few different types of visualizations you can use for labeling objects after identifying them. There are optional functions that can draw multiple bounding boxes and/or write multiple labels on the same image, but it is advisable to use the above functions in a loop in order to have...
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  • 6
    PEFT

    PEFT

    State-of-the-art Parameter-Efficient Fine-Tuning

    Parameter-Efficient Fine-Tuning (PEFT) methods enable efficient adaptation of pre-trained language models (PLMs) to various downstream applications without fine-tuning all the model's parameters. Fine-tuning large-scale PLMs is often prohibitively costly. In this regard, PEFT methods only fine-tune a small number of (extra) model parameters, thereby greatly decreasing the computational and storage costs. Recent State-of-the-Art PEFT techniques achieve performance comparable to that of full...
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  • 7
    Cherche

    Cherche

    Neural Search

    Cherche allows the creation of efficient neural search pipelines using retrievers and pre-trained language models as rankers. Cherche's main strength is its ability to build diverse and end-to-end pipelines from lexical matching, semantic matching, and collaborative filtering-based models. Cherche provides modules dedicated to summarization and question answering. These modules are compatible with Hugging Face's pre-trained models and fully integrated into neural search pipelines. Search is...
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  • 8
    x-transformers

    x-transformers

    A simple but complete full-attention transformer

    A simple but complete full-attention transformer with a set of promising experimental features from various papers. Proposes adding learned memory key/values prior to attending. They were able to remove feedforwards altogether and attain a similar performance to the original transformers. I have found that keeping the feedforwards and adding the memory key/values leads to even better performance. Proposes adding learned tokens, akin to CLS tokens, named memory tokens, that is passed through...
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  • 9
    VisualDL

    VisualDL

    Deep Learning Visualization Toolkit

    VisualDL, a visualization analysis tool of PaddlePaddle, provides a variety of charts to show the trends of parameters and visualizes model structures, data samples, histograms of tensors, PR curves , ROC curves and high-dimensional data distributions. It enables users to understand the training process and the model structure more clearly and intuitively so as to optimize models efficiently. VisualDL provides various visualization functions, including tracking metrics in real-time,...
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    MongoDB Atlas runs apps anywhere

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  • 10
    AutoKeras

    AutoKeras

    AutoML library for deep learning

    AutoKeras: An AutoML system based on Keras. It is developed by DATA Lab at Texas A&M University. The goal of AutoKeras is to make machine learning accessible to everyone. AutoKeras only support Python 3. If you followed previous steps to use virtualenv to install tensorflow, you can just activate the virtualenv. Currently, AutoKeras is only compatible with Python >= 3.7 and TensorFlow >= 2.8.0. AutoKeras supports several tasks with extremely simple interface. AutoKeras would search for the...
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  • 11
    FinMind

    FinMind

    Open Data, more than 50 financial data

    In the era of big data, data is the foundation of everything. We collect more than 50 kinds of Taiwan stock related information and provide download, online analysis, and backtesting. Regardless of the program, you can download data through the api provided by FinMind, or you can download data directly from the website. After data is available, statistical analysis, regression analysis, time series analysis, machine learning, and deep learning can be performed. For individual stocks, provide...
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  • 12
    Hubot

    Hubot

    A customizable life embetterment robot

    Hubot is a framework to build a custom chat bot, first built by GitHub, Inc. to automate their company chat room. Hubot gives you a very nice base for building your very own robot friend. Hubot comes with a small group of core scripts, including things like posting images, translating languages, and integrating with Google Maps. It's extendable with many other scripts, which make Hubot all the more personalized to fit your organization's needs and culture. Hubot can work on many different...
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  • 13
    .NET for Apache Spark

    .NET for Apache Spark

    A free, open-source, and cross-platform big data analytics framework

    ...This means you can use .NET for Apache Spark anywhere you write .NET code allowing you to reuse all the knowledge, skills, code, and libraries you already have as a .NET developer. .NET for Apache Spark runs on Windows, Linux, and macOS using .NET Core, or Windows using .NET Framework. It also runs on all major cloud providers including Azure HDInsight Spark, Amazon EMR Spark, AWS & Azure Databricks.
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  • 14
    dlib

    dlib

    Toolkit for making machine learning and data analysis applications

    ...Dlib's open source licensing allows you to use it in any application, free of charge. Good unit test coverage, the ratio of unit test lines of code to library lines of code is about 1 to 4. The library is tested regularly on MS Windows, Linux, and Mac OS X systems. No other packages are required to use the library, only APIs that are provided by an out of the box OS are needed. There is no installation or configure step needed before you can use the library. All operating system specific code is isolated inside the OS abstraction layers which are kept as small as possible.
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  • 15
    ClawSweeper

    ClawSweeper

    ClawSweeper scans all issues and PRs

    ClawSweeper is an AI-assisted maintenance bot that scans GitHub issues and pull requests to suggest which items may be safe to close. It is designed for open-source maintainers who accumulate stale discussions, outdated reports, duplicate requests, or abandoned contributions over time. The project runs across issues and PRs on a scheduled basis, reviewing each item and producing a reasoned recommendation instead of simply closing content automatically. Its goal is to reduce maintainer...
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  • 16
    How to Train Your GPT

    How to Train Your GPT

    Build a modern LLM from scratch. Every line commented

    How to Train Your GPT is an interactive textbook that teaches users how to build, train, and run a modern language model from scratch. It is written for learners with minimal machine-learning background, using simple explanations, commented code, and practical examples. The project covers the same broad family of architecture behind systems such as GPT-style models, LLaMA-style models, Claude-style systems, and Mistral-style models. It includes chapters and topic explainers on tokenizers,...
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  • 17
    Harmonist

    Harmonist

    Portable AI agent orchestration with mechanical protocol enforcement

    Harmonist is a portable multi-agent orchestration framework for AI coding assistants such as Cursor, Claude Code, Copilot, Windsurf, and Aider. It is designed to make agent workflows more reliable by enforcing protocol rules mechanically instead of trusting prompts alone. The framework includes a catalog of specialized agents, validated memory behavior, supply-chain checks, and hooks that gate code-changing turns. If required reviewers do not run, memory is not updated, or shipped files fail...
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  • 18
    Context Hub

    Context Hub

    Makes coding agents get smarter with every task

    Context Hub is a curated documentation system built to help coding agents write more accurate code. It gives agents versioned, language-specific reference material instead of forcing them to rely on noisy web searches or stale model memory. The project includes a CLI called chub that agents can use to search for available docs, fetch specific API guidance, and request only the files they need. It also supports local annotations, allowing an agent to remember project-specific notes, pitfalls,...
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  • 19
    Anything to NotebookLM

    Anything to NotebookLM

    Multi-source content processor for NotebookLM

    Qiaomu Anything to NotebookLM is a Claude Code skill that turns many types of source material into structured NotebookLM-ready outputs. It is built for users who want to convert articles, web pages, videos, PDFs, office files, podcasts, images, and search results into more usable study or presentation formats. The project uses natural-language commands, so the user can ask for a podcast, slide deck, mind map, report, quiz, flashcards, or infographic without manually building the workflow. It...
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  • 20
    Open Vibe

    Open Vibe

    Open Vibe turns Claude Code into a SaaS-building assistant

    Open Vibe is an open-source course and agent workflow that turns Claude Code, Codex, Copilot, Open Code, or another terminal-capable AI coding agent into a SaaS-building assistant. It is built around Open SaaS, a free Wasp-powered SaaS boilerplate, so learners can create a real app while understanding the architecture behind production-ready SaaS systems. The workflow starts with setup instructions that install Node.js, install the Wasp CLI, and verify the local environment. After creating a...
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  • 21
    Claude Code Router

    Claude Code Router

    Use Claude Code as the foundation for coding infrastructure

    Claude Code Router is a tool for routing Claude Code requests to different model providers and customizing how those requests are handled. It acts as a configurable layer between Claude Code and multiple LLM backends, allowing users to control routing, provider selection, transformations, and workflow behavior. The project is useful for developers who want to keep the Claude Code interface while experimenting with different models, cost profiles, and specialized request handling. It supports...
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  • 22
    Kanwas

    Kanwas

    Shared context board for teams and agents

    Kanwas is an open-source shared context board built for teams and AI agents working together in the same workspace. It gives people and agents a common canvas where documents, evidence, decisions, notes, tasks, embeds, and outputs can live side by side. Instead of scattering context across chats, documents, and disconnected tools, Kanwas turns messy collaborative work into a shared visual environment that both humans and agents can read and update. The platform supports real-time...
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  • 23
    sag

    sag

    Like the macOS say command, but with a modern voice

    sag is a command-line text-to-speech utility inspired by the macOS say command but powered by modern ElevenLabs voice synthesis technology. The project allows users to stream synthesized speech directly to speakers, save audio files, or list and manage available voices through a lightweight terminal interface. Designed for speed and convenience, sag supports voice selection, playback rate adjustments, output format inference, and configurable API endpoints for flexible deployment. It...
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  • 24
    RecursiveMAS

    RecursiveMAS

    Offical Implementation for "Recursive Multi-Agent Systems"

    RecursiveMAS is an advanced multi-agent AI framework that introduces a recursive collaboration mechanism to improve reasoning and problem-solving across multiple agents. Instead of treating agents as independent units exchanging text outputs, it connects them through a shared latent computation loop, allowing internal “thought states” to be passed and refined iteratively. This recursive structure enables agents to build on each other’s intermediate reasoning, leading to deeper and more...
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  • 25
    Google Agent Skills

    Google Agent Skills

    Agent Skills for Google products and technologies

    Google Skills is a repository of modular “agent skills” designed to extend AI agents with structured knowledge about Google technologies and workflows. Each skill provides guidance, best practices, and procedural instructions that agents can use to perform tasks more effectively. The repository includes skills for services like BigQuery, Cloud Run, Firebase, and Kubernetes, as well as onboarding and architectural patterns. It is designed to integrate with agent platforms through a...
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