Showing 3029 open source projects for "edex-ui-windows"

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  • 1
    Penzai

    Penzai

    A JAX research toolkit to build, edit, & visualize neural networks

    Penzai, developed by Google DeepMind, is a JAX-based library for representing, visualizing, and manipulating neural network models as functional pytree data structures. It is designed to make machine learning research more interpretable and interactive, particularly for tasks like model surgery, ablation studies, architecture debugging, and interpretability research. Unlike conventional neural network libraries, Penzai exposes the full internal structure of models, enabling fine-grained...
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  • 2
    Multimodal

    Multimodal

    TorchMultimodal is a PyTorch library

    This project, also known as TorchMultimodal, is a PyTorch library for building, training, and experimenting with multimodal, multi-task models at scale. The library provides modular building blocks such as encoders, fusion modules, loss functions, and transformations that support combining modalities (vision, text, audio, etc.) in unified architectures. It includes a collection of ready model classes—like ALBEF, CLIP, BLIP-2, COCA, FLAVA, MDETR, and Omnivore—that serve as reference...
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  • 3
    Courses (Anthropic)

    Courses (Anthropic)

    Anthropic's educational courses

    Anthropic’s courses repository is a growing collection of self-paced learning materials that teach practical AI skills using Claude and the Anthropic API. It’s organized as a sequence of hands-on courses—starting with API fundamentals and prompt engineering—so learners build capability step by step rather than in isolation. Each course mixes short readings with runnable notebooks and exercises, guiding you through concepts like model parameters, streaming, multimodal prompts, structured...
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  • 4
    Smallpond

    Smallpond

    A lightweight data processing framework built on DuckDB and 3FS

    smallpond is a lightweight distributed data processing framework built by DeepSeek, designed to scale DuckDB workloads over clusters using their 3FS (Fire-Flyer File System) backend. The idea is to preserve DuckDB’s fast analytics engine but lift it from single-node to multi-node settings, giving you the ability to operate on large datasets (e.g. petabyte scale) without moving to a heavyweight system like Spark. Users write Python-like code (via DataFrame APIs or SQL strings) to express...
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  • 5
    DeepEP

    DeepEP

    DeepEP: an efficient expert-parallel communication library

    DeepEP is a communication library designed specifically to support Mixture-of-Experts (MoE) and expert parallelism (EP) deployments. Its core role is to implement high-throughput, low-latency all-to-all GPU communication kernels, which handle the dispatching of tokens to different experts (or shards) and then combining expert outputs back into the main data flow. Because MoE architectures require routing inputs to different experts, communication overhead can become a bottleneck — DeepEP...
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  • 6
    PydanticAI

    PydanticAI

    Agent Framework / shim to use Pydantic with LLMs

    When I first found FastAPI, I got it immediately. I was excited to find something so innovative and ergonomic built on Pydantic. Virtually every Agent Framework and LLM library in Python uses Pydantic, but when we began to use LLMs in Pydantic Logfire, I couldn't find anything that gave me the same feeling. PydanticAI is a Python Agent Framework designed to make it less painful to build production-grade applications with Generative AI. Built by the team behind Pydantic (the validation layer...
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  • 7
    Prompt Declaration Language

    Prompt Declaration Language

    Prompt Declaration Language is a declarative prompt programming lang

    LLMs will continue to change the way we build software systems. They are not only useful as coding assistants, providing snipets of code, explanations, and code transformations, but they can also help replace components that could only previously be achieved with rule-based systems. Whether LLMs are used as coding assistants or software components, reliability remains an important concern. LLMs have a textual interface and the structure of useful prompts is not captured formally. Programming...
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  • 8
    AICodeBot

    AICodeBot

    AI-powered tool for developers, simplifying coding tasks

    AICodeBot is a terminal-based coding assistant designed to make your coding life easier. Think of it as your AI version of a pair programmer. Perform code reviews, create helpful commit messages, debug problems, and help you think through building new features. A team member that accelerates the pace of development and helps you write better code. We've planned to build out multiple different interfaces for interacting with AICodeBot. To start, it's a command-line tool that you can install...
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  • 9
    KServe

    KServe

    Standardized Serverless ML Inference Platform on Kubernetes

    KServe provides a Kubernetes Custom Resource Definition for serving machine learning (ML) models on arbitrary frameworks. It aims to solve production model serving use cases by providing performant, high abstraction interfaces for common ML frameworks like Tensorflow, XGBoost, ScikitLearn, PyTorch, and ONNX. It encapsulates the complexity of autoscaling, networking, health checking, and server configuration to bring cutting edge serving features like GPU Autoscaling, Scale to Zero, and...
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  • 10
    Union Pandera

    Union Pandera

    Light-weight, flexible, expressive statistical data testing library

    The open-source framework for precision data testing for data scientists and ML engineers. Pandera provides a simple, flexible, and extensible data-testing framework for validating not only your data but also the functions that produce them. A simple, zero-configuration data testing framework for data scientists and ML engineers seeking correctness. Access a comprehensive suite of built-in tests, or easily create your own validation rules for your specific use cases. Validate the functions...
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  • 11
    SimpleLogin

    SimpleLogin

    The SimpleLogin back-end

    With email aliases, you can be anonymous online and protect your inbox against spams and phishing. Open-source. Made and hosted in Europe. Receive and send emails anonymously. Next time a website asks for your email address, give an alias instead of your real email. Emails sent to an alias are instantly forwarded to your inbox without the sender knowing anything. Just hit "Reply" if you want to reply to a forwarded email: the reply is sent from your alias and your real email stays hidden....
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  • 12
    Firebase Admin Python SDK

    Firebase Admin Python SDK

    Firebase Admin Python SDK

    Firebase provides the tools and infrastructure you need to develop apps, grow your user base, and earn money. The Firebase Admin Python SDK enables access to Firebase services from privileged environments (such as servers or cloud) in Python. Currently this SDK provides Firebase custom authentication support. Create your own simplified admin console to do things like look up user data or change a user's email address for authentication. Access Google Cloud resources like Cloud Storage...
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  • 13
    SublimeLinter-eslint

    SublimeLinter-eslint

    This linter plugin for SublimeLinter provides an interface to ESLint

    This linter plugin for SublimeLinter provides an interface to ESLint. It will be used with "JavaScript" files, but since eslint is pluggable, it can actually lint a variety of other files as well. SublimeLinter will detect some installed local plugins, and thus it should work automatically for e.g. .vue or .ts files. If it works on the command line, there is a chance it works in Sublime without further ado. Make sure the plugins are installed locally colocated to eslint itself. T.i.,...
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  • 14
    django-split-settings

    django-split-settings

    Organize Django settings into multiple files and directories

    Organize Django settings into multiple files and directories. Easily override and modify settings. Use wildcards in settings file paths and mark settings files as optional. Managing Django’s settings might be tricky. There are severals issues which are encountered by any Django developer along the way. First one is caused by the default project structure. Django clearly offers us a single settings.py file. It seams reasonable at the first glance. And it is actually easy to use just after the...
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  • 15
    Django Cachalot

    Django Cachalot

    No effort, no worry, maximum performance

    Caches your Django ORM queries and automatically invalidates them. Cachalot officially supports Python 3.7-3.10 and Django 2.2, 3.2, and 4.0-4.1 with the databases PostgreSQL, SQLite, and MySQL. Note: an upper limit on Django version is set for your safety. Please do not ignore it. To start developing, install the requirements and run the tests via tox. Currently, benchmarks are supported on Linux and Mac/Darwin. You will need a database called "cachalot" on MySQL and PostgreSQL....
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  • 16
    dynaconf

    dynaconf

    Configuration Management for Python

    Inspired by the 12-factor application guide. Settings management (default values, validation, parsing, templating). Protection of sensitive information (passwords/tokens). Multiple file formats toml|yaml|json|ini|py and also customizable loaders. Full support for environment variables to override existing settings (dotenv support included). Optional layered system for multi environments [default, development, testing, production] (also called multi profiles). Built-in support for Hashicorp...
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  • 17
    django-environ

    django-environ

    Django-environ allows you to utilize 12factor inspired environment

    The idea of this package is to unify a lot of packages that make the same stuff: Take a string from os.environ, parse and cast it to some of useful python typed variables. To do that and to use the 12factor approach, some connection strings are expressed as url, so this package can parse it and return a urllib.parse.ParseResult. These strings from os.environ are loaded from a .env file and filled in os.environ with setdefault method, to avoid overwriting the real environment. A similar...
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  • 18
    Avalanche

    Avalanche

    End-to-End Library for Continual Learning based on PyTorch

    Avalanche is an end-to-end Continual Learning library based on Pytorch, born within ContinualAI with the unique goal of providing a shared and collaborative open-source (MIT licensed) codebase for fast prototyping, training and reproducible evaluation of continual learning algorithms. Avalanche can help Continual Learning researchers in several ways. This module maintains a uniform API for data handling: mostly generating a stream of data from one or more datasets. It contains all the major...
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  • 19
    Opacus

    Opacus

    Training PyTorch models with differential privacy

    Opacus is a library that enables training PyTorch models with differential privacy. It supports training with minimal code changes required on the client, has little impact on training performance, and allows the client to online track the privacy budget expended at any given moment. Vectorized per-sample gradient computation that is 10x faster than micro batching. Supports most types of PyTorch models and can be used with minimal modification to the original neural network. Open source,...
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  • 20
    Deepchecks

    Deepchecks

    Test Suites for validating ML models & data

    Deepchecks is the leading tool for testing and for validating your machine learning models and data, and it enables doing so with minimal effort. Deepchecks accompany you through various validation and testing needs such as verifying your data’s integrity, inspecting its distributions, validating data splits, evaluating your model and comparing between different models. While you’re in the research phase, and want to validate your data, find potential methodological problems, and/or validate...
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  • 21
    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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  • 22
    IVY

    IVY

    The Unified Machine Learning Framework

    Take any code that you'd like to include. For example, an existing TensorFlow model, and some useful functions from both PyTorch and NumPy libraries. Choose any framework for writing your higher-level pipeline, including data loading, distributed training, analytics, logging, visualization etc. Choose any backend framework which should be used under the hood, for running this entire pipeline. Choose the most appropriate device or combination of devices for your needs. DeepMind releases an...
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  • 23
    Amazon Braket PennyLane Plugin

    Amazon Braket PennyLane Plugin

    A plugin for allowing Xanadu PennyLane to use Amazon Braket devices

    The Amazon Braket PennyLane plugin offers two Amazon Braket quantum devices to work with PennyLane. The Amazon Braket Python SDK is an open-source library that provides a framework to interact with quantum computing hardware devices and simulators through Amazon Braket. PennyLane is a machine learning library for optimization and automatic differentiation of hybrid quantum-classical computations. Once the Pennylane-Braket plugin is installed, the provided Braket devices can be accessed...
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  • 24
    AWS ParallelCluster Node

    AWS ParallelCluster Node

    Python package installed on the Amazon EC2 instances

    aws-parallelcluster-node is the python package installed on the Amazon EC2 instances launched as part of AWS ParallelCluster. AWS ParallelCluster is an AWS-supported Open Source cluster management tool that makes it easy for you to deploy and manage High-Performance Computing (HPC) clusters in the AWS cloud. Built on the Open Source CfnCluster project, AWS ParallelCluster enables you to quickly build an HPC compute environment in AWS. It automatically sets up the required compute resources...
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  • 25
    NoneBot

    NoneBot

    Asynchronous multi-platform robot framework written in Python

    Use NB-CLI to quickly build your own robot. Plug-in development, modular management. Supports multiple platforms and multiple incident response methods. Asynchronous priority development to improve operational efficiency. Simple and clear dependency injection system, built-in dependency functions reduce user code. NoneBot2 is a modern, cross-platform, and extensible Python chatbot framework. It is based on Python's type annotations and asynchronous features, and can provide convenient and...
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