Showing 355 open source projects for "core gnu/linux"

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  • 1
    LLM Workflow Engine

    LLM Workflow Engine

    Power CLI and Workflow manager for LLMs (core package)

    LLM Workflow Engine is an open-source command-line framework designed to integrate large language models into automated workflows and developer environments. The platform allows users to interact with AI models directly from the terminal, enabling conversational AI access through shell commands and scripts. Instead of focusing solely on chat interactions, the system is built to embed LLM calls into larger automation pipelines where model outputs can drive decision making or trigger...
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  • 2
    PyTorch-Tutorial-2nd

    PyTorch-Tutorial-2nd

    CV, NLP, LLM project applications, and advanced engineering deployment

    PyTorch-Tutorial-2nd is an open-source educational repository that provides structured tutorials for learning deep learning with the PyTorch framework. The project serves as a practical companion to a second edition of a PyTorch learning guide and is designed to help learners understand neural network concepts through hands-on coding examples. The repository covers a wide range of topics including tensor operations, neural network construction, model training workflows, and optimization...
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  • 3
    Nano-vLLM

    Nano-vLLM

    A lightweight vLLM implementation built from scratch

    Nano-vLLM is a lightweight implementation of the vLLM inference engine designed to run large language models efficiently while maintaining a minimal and readable codebase. The project recreates the core functionality of vLLM in a simplified architecture written in approximately a thousand lines of Python, making it easier for developers and researchers to understand how modern LLM inference systems work. Despite its compact design, nano-vllm incorporates advanced optimization techniques such...
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  • 4
    Sandstorm

    Sandstorm

    One API call, pull Claude agent, completely sandboxed

    Sandstorm is an open-source project that wraps a powerful Claude-based AI agent within a completely sandboxed, ephemeral API service designed to make agentic AI workflows easy to deploy and scale without infrastructure complexity. The core idea is to provide “one API call” access to a robust Claude agent loop that runs inside a secure sandbox, so you can upload files, connect tools, and run long-running tasks — all managed behind a simple REST-style interface that disappears when the work is...
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  • 5
    WorldGen

    WorldGen

    Generate Any 3D Scene in Seconds

    WorldGen is an AI model and library that can generate full 3D scenes in a matter of seconds from either text prompts or reference images. It is designed to create interactive environments suitable for games, simulations, robotics research, and virtual reality, rather than just static 3D assets. The core idea is that you describe a world in natural language and WorldGen produces a navigable 3D scene that you can freely explore in 360 degrees, with loop closure so that the space remains...
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  • 6
    Vision Transformer Pytorch

    Vision Transformer Pytorch

    Implementation of Vision Transformer, a simple way to achieve SOTA

    This repository provides a from-scratch, minimalist implementation of the Vision Transformer (ViT) in PyTorch, focusing on the core architectural pieces needed for image classification. It breaks down the model into patch embedding, positional encoding, multi-head self-attention, feed-forward blocks, and a classification head so you can understand each component in isolation. The code is intentionally compact and modular, which makes it easy to tinker with hyperparameters, depth, width, and...
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  • 7
    ML Ferret

    ML Ferret

    Refer and Ground Anything Anywhere at Any Granularity

    Ferret is Apple’s end-to-end multimodal large language model designed specifically for flexible referring and grounding: it can understand references of any granularity (boxes, points, free-form regions) and then ground open-vocabulary descriptions back onto the image. The core idea is a hybrid region representation that mixes discrete coordinates with continuous visual features, so the model can fluidly handle “any-form” referring while maintaining precise spatial localization. The repo...
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  • 8
    Granite TSFM

    Granite TSFM

    Foundation Models for Time Series

    granite-tsfm collects public notebooks, utilities, and serving components for IBM’s Time Series Foundation Models (TSFM), giving practitioners a practical path from data prep to inference for forecasting and anomaly-detection use cases. The repository focuses on end-to-end workflows: loading data, building datasets, fine-tuning forecasters, running evaluations, and serving models. It documents the currently supported Python versions and points users to where the core TSFM models are hosted...
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  • 9
    Inferable

    Inferable

    Inferable is a developer-first AI automation platform

    Create your first AI automation in 60 seconds. Inferable seamlessly integrates with your existing codebase and infrastructure, allowing you to create powerful AI automation without compromising on control or security. Works with your existing codebase. Integrates with your existing services via opt-in. Enforce determinism through source code. Create and manage automation programmatically. You own the computer, in your own infrastructure. Inferable comes out of the box with delightful DX to...
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  • 10
    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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  • 11
    Haiku

    Haiku

    JAX-based neural network library

    Haiku is a library built on top of JAX designed to provide simple, composable abstractions for machine learning research. Haiku is a simple neural network library for JAX that enables users to use familiar object-oriented programming models while allowing full access to JAX’s pure function transformations. Haiku is designed to make the common things we do such as managing model parameters and other model state simpler and similar in spirit to the Sonnet library that has been widely used...
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  • 12
    OpenPipe

    OpenPipe

    Turn expensive prompts into cheap fine-tuned models

    OpenPipe is an open-source platform focused on improving the efficiency and performance of AI systems by transforming expensive prompt-based workflows into optimized, fine-tuned models and reinforcement-trained agents. It provides tools for training language models and agents using real-world feedback, enabling systems to learn from interactions and improve over time rather than relying solely on static prompts. One of its core components, the Agent Reinforcement Trainer, allows developers...
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  • 13
    Machine Learning for Software Engineers

    Machine Learning for Software Engineers

    A complete daily plan for studying to become a machine learning engine

    Machine Learning for Software Engineers is an open-source learning roadmap designed to help software engineers transition into machine learning roles through a structured, practical study plan. The repository presents a top-down learning path that emphasizes hands-on experience rather than heavy theoretical prerequisites, making it particularly approachable for developers who already have programming experience but limited formal training in machine learning. The project organizes a...
    Downloads: 1 This Week
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  • 14
    LOTUS

    LOTUS

    AI-Powered Data Processing: Use LOTUS to process all of your datasets

    LOTUS is an open-source framework and query engine designed to enable efficient processing of structured and unstructured datasets using large language models. The system provides a declarative programming model that allows developers to express complex AI data operations using high-level commands rather than manually orchestrating model calls. It offers a Python interface with a Pandas-like API, making it familiar for data scientists and engineers already working with data analysis...
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  • 15
    kagent

    kagent

    Kubernetes native framework for building AI agents

    Kagent is a Kubernetes-native framework for building, deploying, and operating AI agents as first-class cloud-native workloads. It models core agent concepts declaratively using Kubernetes custom resources, so teams can manage agents similarly to other platform components via YAML, controllers, and standard cluster workflows. In kagent’s design, an “Agent” represents a system prompt plus a set of tools and other agents, along with an LLM configuration, making the agent definition portable...
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  • 16
    Janus

    Janus

    Unified Multimodal Understanding and Generation Models

    Janus is a sophisticated open-source project from DeepSeek AI that aims to unify both visual understanding and image generation in a single model architecture. Rather than having separate systems for “look and describe” and “prompt and generate”, Janus uses an autoregressive transformer framework with a decoupled visual encoder—allowing it to ingest images for comprehension and to produce images from text prompts with shared internal representations. The design tackles long-standing...
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  • 17
    Griptape

    Griptape

    Python framework for AI workflows and pipelines with chain of thought

    The Griptape framework provides developers with the ability to create AI systems that operate across two dimensions: predictability and creativity. For predictability, Griptape enforces structures like sequential pipelines, DAG-based workflows, and long-term memory. To facilitate creativity, Griptape safely prompts LLMs with tools (keeping output data off prompt by using short-term memory), which connects them to external APIs and data stores. The framework allows developers to transition...
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  • 18
    PaddleNLP

    PaddleNLP

    Easy-to-use and powerful NLP library with Awesome model zoo

    PaddleNLP It is a natural language processing development library for flying paddles, with Easy-to-use text area API, Examples of applications for multiple scenarios, and High-performance distributed training Three major features, aimed at improving the modeling efficiency of the flying oar developer's text field, aiming to improve the developer's development efficiency in the text field, and provide rich examples of NLP applications. Provide rich industry-level pre-task capabilities...
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  • 19
    PennyLane

    PennyLane

    A cross-platform Python library for differentiable programming

    A cross-platform Python library for differentiable programming of quantum computers. Train a quantum computer the same way as a neural network. Built-in automatic differentiation of quantum circuits, using the near-term quantum devices directly. You can combine multiple quantum devices with classical processing arbitrarily! Support for hybrid quantum and classical models, and compatible with existing machine learning libraries. Quantum circuits can be set up to interface with either NumPy,...
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  • 20
    GluonTS

    GluonTS

    Probabilistic time series modeling in Python

    GluonTS is a Python package for probabilistic time series modeling, focusing on deep learning based models. GluonTS requires Python 3.6 or newer, and the easiest way to install it is via pip. We train a DeepAR-model and make predictions using the simple "airpassengers" dataset. The dataset consists of a single time-series, containing monthly international passengers between the years 1949 and 1960, a total of 144 values (12 years * 12 months). We split the dataset into train and test parts,...
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  • 21
    DotVVM

    DotVVM

    Open source MVVM framework for Web Apps

    DotVVM is an open-source framework for ASP.NET. It lets you create web apps using the MVVM pattern, with just C# and HTML. DotVVM can be used to build new ASP.NET Core web apps, or to modernize legacy ASP.NET apps and migrate them to .NET 5. Save your time with GridView, FileUpload and other components shipped with the framework. Don't spend the time building an API. Just load data from the database and use data-binding to display them. DotVVM needs less than 100 kB of JavaScript code. It's...
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  • 22
    Recommenders

    Recommenders

    Best practices on recommendation systems

    The Recommenders repository provides examples and best practices for building recommendation systems, provided as Jupyter notebooks. The module reco_utils contains functions to simplify common tasks used when developing and evaluating recommender systems. Several utilities are provided in reco_utils to support common tasks such as loading datasets in the format expected by different algorithms, evaluating model outputs, and splitting training/test data. Implementations of several...
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  • 23
    Lightly

    Lightly

    A python library for self-supervised learning on images

    ...Our solution can be applied before any data annotation step and the learned representations can be used to visualize and analyze datasets. This allows selecting the best core set of samples for model training through advanced filtering. We provide PyTorch, PyTorch Lightning and PyTorch Lightning distributed examples for each of the models to kickstart your project. Lightly requires Python 3.6+ but we recommend using Python 3.7+. We recommend installing Lightly in a Linux or OSX environment. With lightly, you can use the latest self-supervised learning methods in a modular way using the full power of PyTorch. ...
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  • 24
    Bailing

    Bailing

    Bailing is a voice dialogue robot similar to GPT-4o

    Bailing is an open-source voice-dialogue assistant designed to deliver natural voice-based conversations by combining automatic speech recognition (ASR), voice activity detection (VAD), a large language model (LLM), and text-to-speech (TTS) in a single pipeline. Its goal is to offer a “voice-first” chat experience similar to what one might expect from a system like GPT-4o, but fully open and deployable by users. The project is modular: each core function — ASR, VAD, LLM, TTS — exists as a...
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  • 25
    Mastra

    Mastra

    The TypeScript AI agent framework

    Mastra is a TypeScript-first framework for building AI-powered applications and agents, designed to take projects from prototype to production on a modern JavaScript/TypeScript stack. It integrates cleanly with React, Next.js, and Node-based backends, but can also run as a standalone server, giving teams flexibility in how they deploy their AI logic. At its core, Mastra provides abstractions for agents, workflows, tools, memory, retrieval, and model routing, so developers can focus on...
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