Showing 1139 open source projects for "using"

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  • AI-generated apps that pass security review Icon
    AI-generated apps that pass security review

    Stop waiting on engineering. Build production-ready internal tools with AI—on your company data, in your cloud.

    Retool lets you generate dashboards, admin panels, and workflows directly on your data. Type something like “Build me a revenue dashboard on my Stripe data” and get a working app with security, permissions, and compliance built in from day one. Whether on our cloud or self-hosted, create the internal software your team needs without compromising enterprise standards or control.
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  • Atera all-in-one platform IT management software with AI agents Icon
    Atera all-in-one platform IT management software with AI agents

    Ideal for internal IT departments or managed service providers (MSPs)

    Atera’s AI agents don’t just assist, they act. From detection to resolution, they handle incidents and requests instantly, taking your IT management from automated to autonomous.
    Learn More
  • 1
    SuperDuperDB

    SuperDuperDB

    Integrate, train and manage any AI models and APIs with your database

    Build and manage AI applications easily without needing to move your data to complex pipelines and specialized vector databases. Integrate AI and vector search directly with your database including real-time inference and model training. Just using Python. A single scalable deployment of all your AI models and APIs which is automatically kept up-to-date as new data is processed immediately. No need to introduce an additional database and duplicate your data to use vector search and build on top of it. SuperDuperDB enables vector search in your existing database. Integrate and combine models from Sklearn, PyTorch, HuggingFace with AI APIs such as OpenAI to build even the most complex AI applications and workflows. ...
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  • 2
    Griptape

    Griptape

    Python framework for AI workflows and pipelines with chain of thought

    ...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 between those two dimensions effortlessly based on their use case. Griptape not only helps developers harness the potential of LLMs but also enforces trust boundaries, schema validation, and tool activity-level permissions. ...
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  • 3
    gptcommit

    gptcommit

    A git prepare-commit-msg hook for authoring commit messages with GPT-3

    ...With this tool, you can easily generate clear, comprehensive and descriptive commit messages letting you focus on writing code. To use gptcommit, simply run git commit as you normally would. The hook will automatically generate a commit message for you using a large language model like GPT. If you're not satisfied with the generated message, you can always edit it before committing. By default, gptcommit uses the GPT-3 model. Please ensure you have sufficient credits in your OpenAI account to use it. Commit messages are a key channel for developers to communicate their work with others, especially in code reviews. ...
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  • 4
    Orion

    Orion

    A machine learning library for detecting anomalies in signals

    Orion is a machine-learning library built for unsupervised time series anomaly detection. Such signals are generated by a wide variety of systems, few examples include telemetry data generated by satellites, signals from wind turbines, and even stock market price tickers. We built this to provide one place where users can find the latest and greatest in machine learning and deep learning world including our own innovations. Abstract away from the users the nitty-gritty about preprocessing,...
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  • Outgrown Windows Task Scheduler? Icon
    Outgrown Windows Task Scheduler?

    Free diagnostic identifies where your workflow is breaking down—with instant analysis of your scheduling environment.

    Windows Task Scheduler wasn't built for complex, cross-platform automation. Get a free diagnostic that shows exactly where things are failing and provides remediation recommendations. Interactive HTML report delivered in minutes.
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  • 5
    NannyML

    NannyML

    Detecting silent model failure. NannyML estimates performance

    ...NannyML closes the loop with performance monitoring and post deployment data science, empowering data scientist to quickly understand and automatically detect silent model failure. By using NannyML, data scientists can finally maintain complete visibility and trust in their deployed machine learning models. When the actual outcome of your deployed prediction models is delayed, or even when post-deployment target labels are completely absent, you can use NannyML's CBPE-algorithm to estimate model performance.
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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

    ...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, table-wise, row-wise, table-wise-row-wise, and column-wise sharding. The TorchRec planner can automatically generate optimized sharding plans for models. Pipelined training overlaps dataloading device transfer (copy to GPU), inter-device communications (input_dist), and computation (forward, backward) for increased performance. ...
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  • 8
    Pytorch-toolbelt

    Pytorch-toolbelt

    PyTorch extensions for fast R&D prototyping and Kaggle farming

    A pytorch-toolbelt is a Python library with a set of bells and whistles for PyTorch for fast R&D prototyping and Kaggle farming. Easy model building using flexible encoder-decoder architecture. Modules: CoordConv, SCSE, Hypercolumn, Depthwise separable convolution and more. GPU-friendly test-time augmentation TTA for segmentation and classification. GPU-friendly inference on huge (5000x5000) images. Every-day common routines (fix/restore random seed, filesystem utils, metrics). Losses: BinaryFocalLoss, Focal, ReducedFocal, Lovasz, Jaccard and Dice losses, Wing Loss and more. ...
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  • 9
    Petastorm

    Petastorm

    Petastorm library enables single machine or distributed training

    ...Petastorm supports popular Python-based machine learning (ML) frameworks such as Tensorflow, PyTorch, and PySpark. It can also be used from pure Python code. A dataset created using Petastorm is stored in Apache Parquet format. On top of a Parquet schema, petastorm also stores higher-level schema information that makes multidimensional arrays into a native part of a petastorm dataset. Petastorm supports extensible data codecs. These enable a user to use one of the standard data compressions (jpeg, png) or implement her own.
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  • Axe Credit Portal - ACP- is axefinance’s future-proof AI-driven solution to digitalize the loan process from KYC to servicing, available as a locally hosted or cloud-based software. Icon
    Axe Credit Portal - ACP- is axefinance’s future-proof AI-driven solution to digitalize the loan process from KYC to servicing, available as a locally hosted or cloud-based software.

    Banks, lending institutions

    Founded in 2004, axefinance is a global market-leading software provider focused on credit risk automation for lenders looking to provide an efficient, competitive, and seamless omnichannel financing journey for all client segments (FI, Retail, Commercial, and Corporate.)
    Learn More
  • 10
    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, PyTorch, JAX, or TensorFlow, allowing hybrid CPU-GPU-QPU computations. ...
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  • 11
    Gen.jl

    Gen.jl

    A general-purpose probabilistic programming system

    ...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 for writing down generative models, inference models, variational families, and proposal distributions using ordinary code. But it also lets users migrate parts of their model or inference algorithm to specialized modeling languages for which it can generate especially fast code. Users can also hand-code parts of their models that demand better performance. Neural network inference is fast, but can be inaccurate on out-of-distribution data, and requires expensive training.
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  • 12
    PySyft

    PySyft

    Data science on data without acquiring a copy

    ...However, this means that you cannot compute on information without first obtaining (at least partial) ownership of that information. It also means that you cannot compute using machines without first obtaining control over those machines. This is very limiting to human collaboration and systematically drives the centralization of data, because you cannot work with a bunch of data without first putting it all in one (central) place. The Syft ecosystem seeks to change this system, allowing you to write software which can compute over information you do not own on machines you do not have (total) control over. ...
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  • 13
    Java Telegram Bot API

    Java Telegram Bot API

    Telegram Bot API for Java

    Bots are third-party applications that run inside Telegram. Users can interact with bots by sending them messages, commands and inline requests. You control your bots using HTTPS requests to Telegram's Bot API. Get customized notifications and news. A bot can act as a smart newspaper, sending you relevant content as soon as it's published. Integrate with other services. A bot can enrich Telegram chats with content from external services. Accept payments from Telegram users. A bot can offer paid services or work as a virtual storefront. ...
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  • 14
    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.
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  • 15
    TensorFlow Serving

    TensorFlow Serving

    Serving system for machine learning models

    ...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 easiest and most straight-forward way of using TensorFlow Serving is with Docker images. We highly recommend this route unless you have specific needs that are not addressed by running in a container. In order to serve a Tensorflow model, simply export a SavedModel from your Tensorflow program. SavedModel is a language-neutral, recoverable, hermetic serialization format that enables higher-level systems and tools to produce, consume, and transform TensorFlow models.
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  • 16
    SentenceTransformers

    SentenceTransformers

    Multilingual sentence & image embeddings with BERT

    SentenceTransformers is a Python framework for state-of-the-art sentence, text and image embeddings. The initial work is described in our paper Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. You can use this framework to compute sentence / text embeddings for more than 100 languages. These embeddings can then be compared e.g. with cosine-similarity to find sentences with a similar meaning. This can be useful for semantic textual similar, semantic search, or paraphrase mining. The framework is based on PyTorch and Transformers and offers a large collection of pre-trained models tuned for various tasks. ...
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  • 17
    Groq TypeScript / Node.s

    Groq TypeScript / Node.s

    The official Node.js / Typescript library for the Groq API

    ...It exports strongly-typed interfaces for models, chat completions, file uploads (e.g. for audio transcription), and other endpoints, allowing for better type safety and developer experience when using Groq from TypeScript. The library also supports passing different input types (file streams, blobs, fetch responses) for media-related endpoints, making it flexible for diverse environments (backend, browser, serverless). With this SDK, developers can call Groq’s models, transcribe audio, perform file uploads — all with minimal boilerplate — which streamlines creation of AI-enabled applications in the JavaScript/TypeScript ecosystem.
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  • 18
    Groq Python

    Groq Python

    The official Python Library for the Groq API

    ...Through this library, you can call Groq’s models from Python code — for example to request chat completions, code generation, transcription, or any supported endpoint — using idiomatic Python syntax. The SDK handles authentication (via environment variable or parameter), defines proper type-safe request/response data types, and supports both synchronous and asynchronous usage patterns depending on your application needs. This makes it easy to integrate Groq-powered AI capabilities into backend services, data pipelines, research notebooks, or applications written in Python. ...
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  • 19
    1D Visual Tokenization and Generation

    1D Visual Tokenization and Generation

    This repo contains the code for 1D tokenizer and generator

    The 1D Visual Tokenization and Generation project from ByteDance introduces a novel “one-dimensional” tokenizer designed for images: instead of representing images with large grids of 2D tokens (as in many prior generative/image-modeling systems), it compresses images into as few as 32 discrete tokens (or more, optionally) — thereby achieving a very compact, efficient representation that drastically speeds up generation and reconstruction while retaining strong fidelity. This compact...
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  • 20
    InfiniteYou

    InfiniteYou

    Flexible Photo Recrafting While Preserving Your Identity

    InfiniteYou is an open-source image-generation and “identity-preserving image editing / generation” framework from ByteDance, designed to generate high-fidelity images that preserve a subject’s identity while allowing flexible editing or re-creation according to textual prompts. Using an architecture built around diffusion transformers (DiTs), InfiniteYou introduces a component called InfuseNet that injects identity features derived from reference images into the generation process — via residual connections — so that the output matches the person’s identity closely, without sacrificing visual quality or text-image alignment. ...
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  • 21
    MARS5

    MARS5

    MARS5 speech model (TTS) from CAMB.AI

    MARS5-TTS is CAMB.AI’s open-source English speech model designed for high-quality text-to-speech and voice emulation. It uses a two-stage architecture that combines an autoregressive (AR) model with a non-autoregressive (NAR) model, giving it both expressiveness and speed. The model is built to handle prosodically challenging content such as sports commentary, anime dialogue, and other high-energy or highly varied speech patterns with realistic rhythm and intonation. To control speaker...
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  • 22
    AI Logo Generator

    AI Logo Generator

    A free + OSS logo generator powered by Flux on Together AI

    AI Logo Generator is an open-source AI logo generator that lets you create professional-looking logos in seconds from a simple text prompt. It uses the Flux Pro 1.1 model hosted on Together AI to generate logos, so the heavy lifting is done by a state-of-the-art image model while the app focuses on UX and workflow. The project is built with Next.js and TypeScript, and it uses shadcn/ui plus Tailwind CSS for a modern, responsive interface that feels like a polished SaaS product rather than a...
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  • 23
    Learn AI Engineering

    Learn AI Engineering

    Learn AI and LLMs from scratch using free resources

    Learn AI Engineering is a learning path for AI engineering that consolidates high-quality, free resources across the full stack: math, Python foundations, machine learning, deep learning, LLMs, agents, tooling, and deployment. Rather than a loose bookmark list, it organizes topics into a progression so learners can start from fundamentals and move toward practical, production-oriented skills. It mixes courses, articles, code labs, and videos, emphasizing materials that teach both concepts...
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  • 24
    VoltAgent

    VoltAgent

    Open Source TypeScript AI Agent Framework

    An AI Agent Framework provides the foundational structure and tools needed to build applications powered by autonomous agents. These agents, often driven by Large Language Models (LLMs), can perceive their environment, make decisions, and take actions to achieve specific goals. Building such agents from scratch involves managing complex interactions with LLMs, handling state, connecting to external tools and data, and orchestrating workflows. VoltAgent is an open source TypeScript framework...
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  • 25
    Tiny CUDA Neural Networks

    Tiny CUDA Neural Networks

    Lightning fast C++/CUDA neural network framework

    ...Lower-end cards must reduce the n_neurons parameter or use the CutlassMLP (better compatibility but slower) instead. tiny-cuda-nn comes with a PyTorch extension that allows using the fast MLPs and input encodings from within a Python context. These bindings can be significantly faster than full Python implementations; in particular for the multiresolution hash encoding.
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