Showing 810 open source projects for "open any file"

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  • SKUDONET Open Source Load Balancer Icon
    SKUDONET Open Source Load Balancer

    Take advantage of Open Source Load Balancer to elevate your business security and IT infrastructure with a custom ADC Solution.

    SKUDONET ADC, operates at the application layer, efficiently distributing network load and application load across multiple servers. This not only enhances the performance of your application but also ensures that your web servers can handle more traffic seamlessly.
  • Digital Payments by Deluxe Payment Exchange Icon
    Digital Payments by Deluxe Payment Exchange

    A single integrated payables solution that takes manual payment processes out of the equation, helping reduce risk and cutting costs for your business

    Save time, money and your sanity. Deluxe Payment Exchange+ (DPX+) is our integrated payments solution that streamlines and automates your accounts payable (AP) disbursements. DPX+ ensures secure payments and offers suppliers alternate ways to receive funds, including mailed checks, ACH, virtual credit cards, debit cards, or eCheck payments. By simply integrating with your existing accounting software like QuickBooks®, you’ll implement efficient payment solutions for AP with ease—without costly development fees or untimely delays.
  • 1
    Swirl

    Swirl

    Swirl queries any number of data sources with APIs

    Swirl queries any number of data sources with APIs and uses spaCy and NLTK to re-rank the unified results without extracting and indexing anything! Includes zero-code configs for Apache Solr, ChatGPT, Elastic Search, OpenSearch, PostgreSQL, Google BigQuery, RequestsGet, Google PSE, NLResearch.com, Miro & more! SWIRL adapts and distributes queries to anything with a search API - search engines, databases, noSQL engines, cloud/SaaS services etc - and uses AI (Large Language Models) to re-rank...
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  • 2
    BetaML.jl

    BetaML.jl

    Beta Machine Learning Toolkit

    The Beta Machine Learning Toolkit is a package including many algorithms and utilities to implement machine learning workflows in Julia, Python, R and any other language with a Julia binding. All models are implemented entirely in Julia and are hosted in the repository itself (i.e. they are not wrapper to third-party models). If your favorite option or model is missing, you can try to implement it yourself and open a pull request to share it (see the section Contribute below) or request its...
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  • 3
    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 Inference...
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  • 4
    Sockeye

    Sockeye

    Sequence-to-sequence framework, focused on Neural Machine Translation

    Sockeye is an open-source sequence-to-sequence framework for Neural Machine Translation built on PyTorch. It implements distributed training and optimized inference for state-of-the-art models, powering Amazon Translate and other MT applications. For a quickstart guide to training a standard NMT model on any size of data, see the WMT 2014 English-German tutorial. If you are interested in collaborating or have any questions, please submit a pull request or issue. You can also send questions...
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  • Event Management Software Icon
    Event Management Software

    Ideal for conference and event planners, independent planners, associations, event management companies, non-profits, and more.

    YesEvents offers a comprehensive suite of services that spans the entire conference lifecycle and ensures every detail is executed with precision. Our commitment to exceptional customer service extends beyond conventional boundaries, consistently exceeding expectations and enriching both organizer and attendee experiences.
  • 5
    Metarank

    Metarank

    A low code Machine Learning service that personalizes articles

    Metarank is a service that can personalize any type of content: product listings, articles, recommendations and search results in 3 easy steps with a few lines of code. It’s often considered "too risky" to spend 6+ months on an in-house moonshot project to reinvent the wheel without an experienced team and no existing open-source tools. Metarank makes it easy not only for Amazon to do personalization but for everyone else. Ingest historical item listings, clicks and item metadata so Metarank...
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  • 6
    Aim

    Aim

    An easy-to-use & supercharged open-source experiment tracker

    Aim logs all your AI metadata (experiments, prompts, etc) enabling a UI to compare & observe them and SDK to query them programmatically. The Aim standard package comes with all integrations. If you'd like to modify the integration and make it custom, create a new integration package and share with others. Aim is an open-source, self-hosted AI Metadata tracking tool designed to handle 100,000s of tracked metadata sequences. The two most famous AI metadata applications are: experiment tracking...
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  • 7
    Dough

    Dough

    Dough is a open source tool for steering AI animations with precision

    We believe that AI has the potential to allow billions to experience creative fulfillment this century. However, in order to reach this potential, artistic control is key - it's the difference between something feeling like it was made by you rather than for you. To unlock the multitude of control types and artistic flows possible with AI, we want to build tooling and infrastructure to empower a community of tool-builders, who in turn empower a world of budding artists. If you have a...
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  • 8
    CleanRL

    CleanRL

    High-quality single file implementation of Deep Reinforcement Learning

    CleanRL is a Deep Reinforcement Learning library that provides high-quality single-file implementation with research-friendly features. The implementation is clean and simple, yet we can scale it to run thousands of experiments using AWS Batch. CleanRL is not a modular library and therefore it is not meant to be imported. At the cost of duplicate code, we make all implementation details of a DRL algorithm variant easy to understand, so CleanRL comes with its own pros and cons. You should...
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  • 9
    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...
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  • AI-powered conversation intelligence software Icon
    AI-powered conversation intelligence software

    Unlock call analytics that provide actionable insights with our call tracking software, empowering you to identify what's working and what's not.

    Every customer interaction is vital to your business success and revenue growth. With Jiminny’s AI-powered conversation intelligence software, we take recording, capturing, and meticulous analysis of call recordings to the next level. Unlock call analytics that provide actionable insights with our call tracking software, empowering you to identify what's working and what's not. Seamlessly support your biggest objectives across the entire business landscape with our innovative call tracking system.
  • 10
    Marvin

    Marvin

    A batteries-included library for building AI-powered software

    Meet Marvin: a batteries-included library for building AI-powered software. Marvin's job is to integrate AI directly into your codebase by making it look and feel like any other function. Marvin introduces a new concept called AI Functions. These functions differ from conventional ones in that they don’t rely on source code, but instead generate their outputs on-demand through AI. With AI functions, you don't have to write complex code for tasks like extracting entities from web pages, scoring...
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  • 11
    GPTel

    GPTel

    A no-frills ChatGPT client for Emacs

    GPTel is a simple, no-frills ChatGPT client for Emacs. No external dependencies, only Emacs. Also, it’s async. Interact with ChatGPT from any buffer in Emacs. ChatGPT’s responses are in Markdown or Org markup (configurable). Supports conversations (not just one-off queries) and multiple independent sessions. You can go back and edit your previous prompts, or even ChatGPT’s previous responses when continuing a conversation. These will be fed back to ChatGPT. Run M-x gptel to start or switch...
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  • 12
    Django friendly finite state machine

    Django friendly finite state machine

    Django friendly finite state machine support

    Django-fsm adds simple declarative state management for Django models. If you need parallel task execution, view, and background task code reuse over different flows - check my new project Django-view flow. Instead of adding a state field to a Django model and managing its values by hand, you use FSMField and mark model methods with the transition decorator. These methods could contain side effects of the state change. You may also take a look at the Django-fsm-admin project containing a...
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  • 13
    talos

    talos

    Hyperparameter Optimization for TensorFlow, Keras and PyTorch

    ... solutions that add complexity instead of reducing it. Within minutes, without learning any new syntax, Talos allows you to configure, perform, and evaluate hyperparameter optimization experiments that yield state-of-the-art results across a wide range of prediction tasks. Talos provides the simplest and yet most powerful available method for hyperparameter optimization with TensorFlow (tf.keras) and PyTorch.
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  • 14
    High-Level Training Utilities Pytorch

    High-Level Training Utilities Pytorch

    High-level training, data augmentation, and utilities for Pytorch

    Contains significant improvements, bug fixes, and additional support. Get it from the releases, or pull the master branch. This package provides a few things. A high-level module for Keras-like training with callbacks, constraints, and regularizers. Comprehensive data augmentation, transforms, sampling, and loading. Utility tensor and variable functions so you don't need numpy as often. Have any feature requests? Submit an issue! I'll make it happen. Specifically, any data augmentation, data...
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  • 15
    BentoML

    BentoML

    Unified Model Serving Framework

    BentoML simplifies ML model deployment and serves your models at a production scale. Support multiple ML frameworks natively: Tensorflow, PyTorch, XGBoost, Scikit-Learn and many more! Define custom serving pipeline with pre-processing, post-processing and ensemble models. Standard .bento format for packaging code, models and dependencies for easy versioning and deployment. Integrate with any training pipeline or ML experimentation platform. Parallelize compute-intense model inference workloads...
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  • 16
    Weights and Biases

    Weights and Biases

    Tool for visualizing and tracking your machine learning experiments

    Use W&B to build better models faster. Track and visualize all the pieces of your machine learning pipeline, from datasets to production models. Quickly identify model regressions. Use W&B to visualize results in real time, all in a central dashboard. Focus on the interesting ML. Spend less time manually tracking results in spreadsheets and text files. Capture dataset versions with W&B Artifacts to identify how changing data affects your resulting models. Reproduce any model, with saved code...
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  • 17
    SageMaker Training Toolkit

    SageMaker Training Toolkit

    Train machine learning models within Docker containers

    ... and reliable training process. The SageMaker Training Toolkit can be easily added to any Docker container, making it compatible with SageMaker for training models. If you use a prebuilt SageMaker Docker image for training, this library may already be included. Write a training script (eg. train.py). Define a container with a Dockerfile that includes the training script and any dependencies.
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  • 18
    Discord4J

    Discord4J

    Reactive library to enable quick and easy development of bots

    ... to Discord's specifications and to provide the least amount of surprises when interacting with our library. Discord4J breaks itself into modules to allow advanced users to interact with our API at lower levels to build minimal and fast runtimes or even add their own abstractions. Discord4J can be used to develop any bot, big or small. We offer many tools for developing large-scale bots from custom distribution frameworks, off-heap caching, and its interaction with Reactor allows complete integration.
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  • 19
    BotKube

    BotKube

    An app that helps you monitor your Kubernetes cluster

    BotKube is a messaging bot for monitoring and debugging Kubernetes clusters. It's built and maintained by InfraCloud. BotKube can be integrated with multiple messaging platforms like - Slack, Mattermost, Microsoft Teams to help you monitor your Kubernetes cluster(s), debug critical deployments and gives recommendations for standard practices by running checks on the Kubernetes resources. BotKube watches Kubernetes resources and sends a notification to the channel if any event occurs for example...
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  • 20
    fastai

    fastai

    Deep learning library

    fastai is a deep learning library which provides practitioners with high-level components that can quickly and easily provide state-of-the-art results in standard deep learning domains, and provides researchers with low-level components that can be mixed and matched to build new approaches. It aims to do both things without substantial compromises in ease of use, flexibility, or performance. This is possible thanks to a carefully layered architecture, which expresses common underlying...
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  • 21
    promptfoo

    promptfoo

    Evaluate and compare LLM outputs, catch regressions, improve prompts

    Ensure high-quality LLM outputs with automatic evals. Use a representative sample of user inputs to reduce subjectivity when tuning prompts. Use built-in metrics, LLM-graded evals, or define your own custom metrics. Compare prompts and model outputs side-by-side, or integrate the library into your existing test/CI workflow. Use OpenAI, Anthropic, and open-source models like Llama and Vicuna, or integrate custom API providers for any LLM API.
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  • 22
    ChatGPT-Reviewer

    ChatGPT-Reviewer

    Automated pull requests reviewing and issues triaging with ChatGPT

    Automated pull requests reviewing and issues triaging with ChatGPT. Create an OpenAI API key here, and then set the key as an action secret in your repository named OPENAI_API_KEY. The ChatGPT reviewer PRs are also getting reviewed by ChatGPT, refer the pull requests for the sample review comments. In order to protect public repositories for malicious users, Github runs all pull request workflows raised from repository forks with a read-only token and no access to secrets.
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  • 23
    BudouX

    BudouX

    Standalone, small, language-neutral

    Standalone. Small. Language-neutral. BudouX is the successor to Budou, the machine learning-powered line break organizer tool. It is standalone. It works with no dependency on third-party word segmenters such as Google cloud natural language API. It is small. It takes only around 15 KB including its machine learning model. It's reasonable to use it even on the client-side. It is language-neutral. You can train a model for any language by feeding a dataset to BudouX’s training script.
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  • 24
    Fairlearn

    Fairlearn

    A Python package to assess and improve fairness of ML models

    Fairlearn is a Python package that empowers developers of artificial intelligence (AI) systems to assess their system's fairness and mitigate any observed unfairness issues. Fairlearn contains mitigation algorithms as well as metrics for model assessment. Besides the source code, this repository also contains Jupyter notebooks with examples of Fairlearn usage. An AI system can behave unfairly for a variety of reasons. In Fairlearn, we define whether an AI system is behaving unfairly in terms...
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  • 25
    FFCV

    FFCV

    Fast Forward Computer Vision (and other ML workloads!)

    ffcv is a drop-in data loading system that dramatically increases data throughput in model training. From gridding to benchmarking to fast research iteration, there are many reasons to want faster model training. Below we present premade codebases for training on ImageNet and CIFAR, including both (a) extensible codebases and (b) numerous premade training configurations.
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