Showing 2660 open source projects for "art-linux"

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  • 1
    Codeflash

    Codeflash

    Optimize your code automatically with AI

    Codeflash is a general-purpose optimizer for Python that uses advanced large language models (LLMs) to automatically generate, test, and benchmark multiple optimization ideas, then creates merge-ready pull requests with the best improvements for your code. Optimize an entire existing codebase by running codeflash --all. Automate optimizing all future code you will write by installing Codeflash as a GitHub action. Optimize a Python workflow python myscript.py end-to-end by running codeflash...
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  • 2
    Notte

    Notte

    Opensource browser using agents

    Notte is an open-source browser framework that enables the development and deployment of web-based AI agents. It introduces a perception layer that transforms web pages into structured, navigable maps described in natural language, allowing agents to interact with the internet more effectively. Notte is designed for building scalable and efficient browser-based AI applications.
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  • 3
    EvoTorch

    EvoTorch

    Advanced evolutionary computation library built on top of PyTorch

    EvoTorch is an evolutionary optimization framework built on top of PyTorch, developed by NNAISENSE. It is designed for large-scale optimization problems, particularly those that require evolutionary algorithms rather than gradient-based methods.
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  • 4
    TFX

    TFX

    TFX is an end-to-end platform for deploying production ML pipelines

    TensorFlow Extended (TFX) is a Google-production-scale machine learning platform based on TensorFlow. It provides a configuration framework to express ML pipelines consisting of TFX components. TFX pipelines can be orchestrated using Apache Airflow and Kubeflow Pipelines. Both the components themselves and the integrations with orchestration systems can be extended. TFX components interact with an ML Metadata backend that keeps a record of component runs, input and output artifacts, and...
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  • 5
    Chronos Forecasting

    Chronos Forecasting

    Pretrained (Language) Models for Probabilistic Time Series Forecasting

    Chronos is a family of pretrained time series forecasting models based on language model architectures. A time series is transformed into a sequence of tokens via scaling and quantization, and a language model is trained on these tokens using the cross-entropy loss. Once trained, probabilistic forecasts are obtained by sampling multiple future trajectories given the historical context. Chronos models have been trained on a large corpus of publicly available time series data, as well as...
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  • 6
    SkyPilot

    SkyPilot

    SkyPilot: Run AI and batch jobs on any infra

    SkyPilot is a framework for running AI and batch workloads on any infra, offering unified execution, high cost savings, and high GPU availability. Run AI and batch jobs on any infra (Kubernetes or 12+ clouds). Get unified execution, cost savings, and high GPU availability via a simple interface.
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  • 7
    omegaml

    omegaml

    MLOps simplified. From ML Pipeline ⇨ Data Product without the hassle

    omega|ml is the innovative Python-native MLOps platform that provides a scalable development and runtime environment for your Data Products. Works from laptop to cloud.
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  • 8
    imodelsX

    imodelsX

    Interpretable prompting and models for NLP

    Interpretable prompting and models for NLP (using large language models). Generates a prompt that explains patterns in data (Official) Explain the difference between two distributions. Find a natural-language prompt using input-gradients. Fit a better linear model using an LLM to extract embeddings. Fit better decision trees using an LLM to expand features. Finetune a single linear layer on top of LLM embeddings. Use these just a like a sci-kit-learn model. During training, they fit better...
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  • 9
    TorchRec

    TorchRec

    Pytorch domain library for recommendation systems

    TorchRec is a PyTorch domain library built to provide common sparsity & parallelism primitives needed for large-scale recommender systems (RecSys). It allows authors to train models with large embedding tables sharded across many GPUs. Parallelism primitives that enable easy authoring of large, performant multi-device/multi-node models using hybrid data-parallelism/model-parallelism. The TorchRec sharder can shard embedding tables with different sharding strategies including data-parallel,...
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  • 10
    Denoising Diffusion Probabilistic Model

    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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  • 11
    OpenChronicle

    OpenChronicle

    Open-source, local-first memory for any tool-capable LLM agent

    OpenChronicle is a knowledge management and storytelling platform designed to organize information into structured timelines and interconnected narratives. It allows users to create chronological records that link events, ideas, and entities in a cohesive format. The system emphasizes visualization and organization of complex information over time. It can be used for research, writing, or personal knowledge tracking. OpenChronicle supports extensibility, enabling customization of how data is...
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  • 12
    nesa

    nesa

    Run AI models end-to-end encrypted

    nesa is an open-source initiative focused on building decentralized AI infrastructure that enables secure, verifiable, and privacy-preserving machine learning and inference across distributed environments. The project aims to address key challenges in modern AI systems, such as data privacy, trust, and centralization, by leveraging cryptographic techniques and decentralized architectures. NESA allows developers to run AI computations in a way that ensures data integrity and confidentiality,...
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  • 13
    Screenshot to Code

    Screenshot to Code

    A neural network that transforms a design mock-up into static websites

    Screenshot-to-code is a tool or prototype that attempts to convert UI screenshots (e.g., of mobile or web UIs) into code representations, likely generating layouts, HTML, CSS, or markup from image inputs. It is part of a research/proof-of-concept domain in UI automation and image-to-UI code generation. Mapping visual design to code constructs. Code/UI layout (HTML, CSS, or markup). Examples/demo scripts showing “image UI code”.
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  • 14
    TreeQuest

    TreeQuest

    A Tree Search Library with Flexible API for LLM Inference-Time Scaling

    TreeQuest, developed by SakanaAI, is a versatile Python library implementing adaptive tree search algorithms—such as AB‑MCTS—for enhancing inference-time performance of large language models (LLMs). It allows developers to define custom state-generation and scoring functions (e.g., via LLMs), and then efficiently explores possible answer trees during runtime. With support for multi-LLM collaboration, checkpointing, and mixed policies, TreeQuest enables smarter, trial‑and‑error question...
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  • 15
    Magentic UI

    Magentic UI

    A research prototype of a human-centered web agent

    Magentic-UI is a research prototype developed by Microsoft that serves as a human-centered interface powered by a multi-agent system. It enables users to automate complex web tasks, such as browsing, form filling, and data analysis, while maintaining control over the process. The system emphasizes transparency and user involvement, making it suitable for tasks requiring both automation and human oversight.
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  • 16
    PilottAI

    PilottAI

    Python framework for building scalable multi-agent systems

    pilottai is an AI-based autonomous drone navigation system utilizing reinforcement learning for real-time decision-making. It is designed for simulating and training drones to fly safely through dynamic environments using AI-based controllers.
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  • 17
    CRAB

    CRAB

    CRAB: Cross-environment Agent Benchmark for Multimodal Language Model

    CRAB (Composable and Reusable Autonomous Bots) is a framework for building modular, reusable AI agents that can perform complex tasks in various domains. It focuses on creating AI-driven workflows that can be composed of multiple autonomous agents working together.
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  • 18
    Automatic text summarizer

    Automatic text summarizer

    Module for automatic summarization of text documents and HTML pages

    Sumy is an automatic text summarization library that provides multiple algorithms for extracting key content from documents and articles. Simple library and command line utility for extracting summary from HTML pages or plain texts. The package also contains a simple evaluation framework for text summaries. Implemented summarization methods are described in the documentation. I also maintain a list of alternative implementations of the summarizers in various programming languages.
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  • 19
    ChatGPT Telegram Bot

    ChatGPT Telegram Bot

    A Telegram bot that integrates with OpenAI's official ChatGPT APIs

    A Telegram bot that integrates with OpenAI's official ChatGPT, DALL·E and Whisper APIs to provide answers. Ready to use with minimal configuration required.
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  • 20
    Prompt flow

    Prompt flow

    Build high-quality LLM apps

    Prompt flow is a suite of development tools designed to streamline the end-to-end development cycle of LLM-based AI applications, from ideation, prototyping, testing, and evaluation to production deployment and monitoring. It makes prompt engineering much easier and enables you to build LLM apps with production quality.
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  • 21
    TorchAudio

    TorchAudio

    Data manipulation and transformation for audio signal processing

    The aim of torchaudio is to apply PyTorch to the audio domain. By supporting PyTorch, torchaudio follows the same philosophy of providing strong GPU acceleration, having a focus on trainable features through the autograd system, and having consistent style (tensor names and dimension names). Therefore, it is primarily a machine learning library and not a general signal processing library. The benefits of PyTorch can be seen in torchaudio through having all the computations be through PyTorch...
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  • 22
    Lightly

    Lightly

    A python library for self-supervised learning on images

    ...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. Experiment with different backbones, models, and loss functions.
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  • 23
    BCEmbedding

    BCEmbedding

    Netease Youdao's open-source embedding and reranker models

    BCEmbedding is NetEase Youdao’s open-source embedding and reranker model project for retrieval-augmented generation workflows. It includes an EmbeddingModel for semantic vector generation and a RerankerModel for refining and ordering search results. The project is optimized for bilingual and cross-lingual retrieval, especially across Chinese and English. It is used as a foundation for RAG systems such as QAnything and other Youdao products. The models are designed to work directly without...
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  • 24
    yourself-skill

    yourself-skill

    Instead of distilling others, it is better to distil yourself

    yourself-skill is an AI skill framework focused on self-reflection and personalization, enabling agents to adapt their behavior based on user context and interaction history. It encourages systems to maintain awareness of user preferences, goals, and communication styles. The project emphasizes building more human-aligned interactions by incorporating memory and contextual reasoning. It can be integrated into broader AI systems to improve personalization and continuity across sessions. The...
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  • 25
    TorchCode

    TorchCode

    Practice implementing softmax, attention, GPT-2 and more

    TorchCode is an interactive learning and practice platform designed to help developers master PyTorch by implementing core machine learning operations and architectures from scratch. It is structured similarly to competitive programming platforms like LeetCode but focuses specifically on tensor operations and deep learning concepts. The platform provides a collection of curated problems that cover fundamental topics such as activation functions, normalization layers, attention mechanisms,...
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