Showing 8133 open source projects for "artificial"

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  • 1
    Manifest

    Manifest

    🦞 Take control of your OpenClaw costs

    Manifest is an open-source OpenClaw plugin designed to help users take control of their LLM costs through intelligent routing and real-time observability. Instead of sending every request to the same large model, Manifest intercepts each query and evaluates it using a 23-dimension scoring algorithm in under 2 milliseconds. It then routes the request to the most cost-effective and suitable model, potentially reducing costs by up to 90%. The platform includes a real-time dashboard that...
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  • 2
    Xorbits Inference

    Xorbits Inference

    Replace OpenAI GPT with another LLM in your app

    Replace OpenAI GPT with another LLM in your app by changing a single line of code. Xinference gives you the freedom to use any LLM you need. With Xinference, you're empowered to run inference with any open-source language models, speech recognition models, and multimodal models, whether in the cloud, on-premises, or even on your laptop. Xorbits Inference(Xinference) is a powerful and versatile library designed to serve language, speech recognition, and multimodal models. With Xorbits...
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  • 3
    LLM Foundry

    LLM Foundry

    LLM training code for MosaicML foundation models

    Introducing MPT-7B, the first entry in our MosaicML Foundation Series. MPT-7B is a transformer trained from scratch on 1T tokens of text and code. It is open source, available for commercial use, and matches the quality of LLaMA-7B. MPT-7B was trained on the MosaicML platform in 9.5 days with zero human intervention at a cost of ~$200k. Large language models (LLMs) are changing the world, but for those outside well-resourced industry labs, it can be extremely difficult to train and deploy...
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  • 4
    Deep Lake

    Deep Lake

    Data Lake for Deep Learning. Build, manage, and query datasets

    Deep Lake (or Deeplake, formerly known as Activeloop Hub) is a data lake for deep learning applications. Our open-source dataset format is optimized for rapid streaming and querying of data while training models at scale, and it includes a simple API for creating, storing, and collaborating on AI datasets of any size. It can be deployed locally or in the cloud, and it enables you to store all of your data in one place, ranging from simple annotations to large videos. Deep Lake is used by...
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  • 5
    Seldon Core

    Seldon Core

    An MLOps framework to package, deploy, monitor and manage models

    The de facto standard open-source platform for rapidly deploying machine learning models on Kubernetes. Seldon Core, our open-source framework, makes it easier and faster to deploy your machine learning models and experiments at scale on Kubernetes. Seldon Core serves models built in any open-source or commercial model building framework. You can make use of powerful Kubernetes features like custom resource definitions to manage model graphs. And then connect your continuous integration and...
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  • 6
    DSharpPlus

    DSharpPlus

    A .NET Standard library for making bots using the Discord API

    All Nightly versions are available on Nuget as a pre-release. These are cutting-edge versions automatically built from the latest commit in the master branch in this repository, and as such always contains the latest changes. If you want to use the latest features on Discord, you should use the nightlies Despite the nature of pre-release software, all changes to the library are held under a level of scrutiny; for this library, unstable does not mean bad quality, rather it means that the API...
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  • 7
    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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  • 8
    Petastorm

    Petastorm

    Petastorm library enables single machine or distributed training

    Petastorm library enables single machine or distributed training and evaluation of deep learning models from datasets in Apache Parquet format. It supports ML frameworks such as Tensorflow, Pytorch, and PySpark and can be used from pure Python code. Petastorm is an open-source data access library developed at Uber ATG. This library enables single machine or distributed training and evaluation of deep learning models directly from datasets in Apache Parquet format. Petastorm supports popular...
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  • 9
    Gen.jl

    Gen.jl

    A general-purpose probabilistic programming system

    An open-source stack for generative modeling and probabilistic inference. Gen’s inference library gives users building blocks for writing efficient probabilistic inference algorithms that are tailored to their models, while automating the tricky math and the low-level implementation details. Gen helps users write hybrid algorithms that combine neural networks, variational inference, sequential Monte Carlo samplers, and Markov chain Monte Carlo. Gen features an easy-to-use modeling language...
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  • 10
    Thinc

    Thinc

    A refreshing functional take on deep learning

    Thinc is a lightweight deep learning library that offers an elegant, type-checked, functional-programming API for composing models, with support for layers defined in other frameworks such as PyTorch, TensorFlow and MXNet. You can use Thinc as an interface layer, a standalone toolkit or a flexible way to develop new models. Previous versions of Thinc have been running quietly in production in thousands of companies, via both spaCy and Prodigy. We wrote the new version to let users compose,...
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  • 11
    MONAI

    MONAI

    AI Toolkit for Healthcare Imaging

    The MONAI framework is the open-source foundation being created by Project MONAI. MONAI is a freely available, community-supported, PyTorch-based framework for deep learning in healthcare imaging. It provides domain-optimized foundational capabilities for developing healthcare imaging training workflows in a native PyTorch paradigm. Project MONAI also includes MONAI Label, an intelligent open source image labeling and learning tool that helps researchers and clinicians collaborate, create...
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  • 12
    SageMaker Hugging Face Inference Toolkit

    SageMaker Hugging Face Inference Toolkit

    Library for serving Transformers models on Amazon SageMaker

    SageMaker Hugging Face Inference Toolkit is an open-source library for serving Transformers models on Amazon SageMaker. This library provides default pre-processing, predict and postprocessing for certain Transformers models and tasks. It utilizes the SageMaker Inference Toolkit for starting up the model server, which is responsible for handling inference requests. For the Dockerfiles used for building SageMaker Hugging Face Containers, see AWS Deep Learning Containers. The SageMaker Hugging...
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  • 13
    Rubix ML

    Rubix ML

    A high-level machine learning and deep learning library for PHP

    Rubix ML is a free open-source machine learning (ML) library that allows you to build programs that learn from your data using the PHP language. We provide tools for the entire machine learning life cycle from ETL to training, cross-validation, and production with over 40 supervised and unsupervised learning algorithms. In addition, we provide tutorials and other educational content to help you get started using ML in your projects. Our intuitive interface is quick to grasp while hiding alot...
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  • 14
    TensorFlow Serving

    TensorFlow Serving

    Serving system for machine learning models

    TensorFlow Serving is a flexible, high-performance serving system for machine learning models, designed for production environments. It deals with the inference aspect of machine learning, taking models after training and managing their lifetimes, providing clients with versioned access via a high-performance, reference-counted lookup table. TensorFlow Serving provides out-of-the-box integration with TensorFlow models, but can be easily extended to serve other types of models and data. The...
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  • 15
    rendergit

    rendergit

    Render any git repo into a single static HTML page for humans or LLMs

    rendergit is a command-line utility that converts an entire Git repository into a single static HTML page. It is designed for developers who want to inspect a codebase without repeatedly navigating through folders and individual files. The generated human-oriented view includes syntax highlighting, rendered Markdown, sidebar navigation, file sizes, and a directory overview. A second LLM-oriented view exposes the repository as CXML text that can be copied into AI assistants for analysis....
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  • 16
    Sinas

    Sinas

    Open-source platform for building AI agents and serverless automation

    Sinas is an open-source platform for building AI agents and serverless automation with fine-grained access control. It provides a self-hosted backend where developers can configure agents, connect LLM providers, write Python functions, and trigger workflows through webhooks or schedules. The platform supports isolated container execution for functions, which helps separate automation logic from the rest of the system. It also includes reusable skills, state stores, document collections,...
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  • 17
    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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  • 18
    AI Coding Dictionary

    AI Coding Dictionary

    AI coding jargon, explained in plain English

    Dictionary of AI Coding is an educational reference project that explains AI coding terminology in plain English. It is designed for developers who use coding agents but feel slowed down by unclear vocabulary, hidden assumptions, confusing billing concepts, and inconsistent model behavior. The dictionary organizes terms across models, context windows, tools, environments, failure modes, handoffs, and related AI coding workflows. Its tone is intentionally direct and accessible, avoiding dense...
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  • 19
    agentic-stack

    agentic-stack

    One brain, many harnesses. Portable .agent/ folder

    agentic-stack is a framework or toolkit designed to build, orchestrate, and deploy AI agents in a structured and scalable way. It likely provides components for managing agent workflows, communication, and task execution across different systems. The project emphasizes modularity, enabling developers to assemble custom pipelines using various AI models, tools, and APIs. It may include abstractions for memory, planning, and tool usage, reflecting modern agentic AI design patterns. The stack...
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  • 20
    ML Intern

    ML Intern

    ML engineer that reads papers, trains models, and ships ML models

    ML Intern is a repository by Hugging Face that provides educational content and projects aimed at helping learners gain practical experience in machine learning and AI development. It is designed to simulate the experience of working as a machine learning intern, offering tasks and exercises that mirror real-world workflows. The project includes tutorials, datasets, and example implementations that guide users through different aspects of ML development. It emphasizes hands-on learning,...
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  • 21
    Riff

    Riff

    Nine opinionated skills for writing personal essays with Claude

    Riff is a development tool designed to enhance coding workflows through AI-assisted features and automation. It provides an environment where developers can interact with code using natural language, enabling faster understanding and modification of projects. The system integrates with language models to generate suggestions, explanations, and improvements based on context. It is built to streamline development processes, reducing the time required for debugging, refactoring, and...
    Downloads: 2 This Week
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  • 22
    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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  • 23
    Writing AI Conference Papers

    Writing AI Conference Papers

    Writing AI Conference Papers: A Handbook for Beginners

    WritingAIPaper is an open-source guide designed to help beginners understand and navigate the process of writing and publishing academic papers in the field of artificial intelligence. The project provides structured guidance on how to transform research ideas into complete manuscripts, covering topics such as defining the core contribution, organizing the paper structure, and refining technical details. It emphasizes practical advice and common pitfalls, making it especially useful for students or early-career researchers who may struggle with academic writing conventions. ...
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  • 24
    SuperPrompt

    SuperPrompt

    Experimental prompt framework exploring reasoning structures in AI

    SuperPrompt is an experimental open source project focused on designing complex prompts intended to help researchers and developers better understand how AI agents reason and respond. It explores structured prompt engineering techniques that combine symbolic expressions, logical constructs, and conceptual frameworks to guide large language models toward deeper reasoning processes. Its main concept revolves around a highly structured prompt format that includes tagged sections for reasoning,...
    Downloads: 3 This Week
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  • 25
    Machine Learning Study

    Machine Learning Study

    This repository is for helping those interested in machine learning

    Machine Learning Study is an educational repository containing tutorials and study materials related to machine learning and data science using Python. The project compiles notebooks, explanatory documents, and practical code examples that illustrate common machine learning workflows. Topics covered include supervised learning algorithms, feature engineering, model training, and performance evaluation techniques. The repository is structured as a learning resource that guides readers through...
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