Showing 10 open source projects for "code editoral software"

View related business solutions
  • See what everyone is allocated to. Projects, clients, meetings - all in one tool. Icon
    See what everyone is allocated to. Projects, clients, meetings - all in one tool.

    The fast, simple way to schedule people, equipment and other resources online.

    Designed to replace clunky, old scheduling spreadsheets, Resource Guru helps managers get organized fast. The platform covers resource planning, resource scheduling, resource management, staff leave management, reporting, and more.
    Free Trial
  • Securely stream and govern industrial data to power intelligent operations with agentic insights. Icon
    Securely stream and govern industrial data to power intelligent operations with agentic insights.

    For IoT Developers, Solution Architects, Technical Architects, CTOs, OT/IT Engineers

    Trusted MQTT Platform — Fully-managed and cloud-native MQTT platform for bi-directional IoT data movement.
    Learn More
  • 1
    CodiumAI PR-Agent

    CodiumAI PR-Agent

    AI-Powered tool for automated pull request analysis

    CodiumAI PR-Agent is an open-source tool aiming to help developers review pull requests faster and more efficiently. It automatically analyzes the pull request and can provide several types of commands. See the Usage Guide for instructions how to run the different tools from CLI, online usage, Or by automatically triggering them when a new PR is opened. You can try GPT-4 powered PR-Agent, on your public GitHub repository, instantly. Just mention @CodiumAI-Agent and add the desired command in...
    Downloads: 1 This Week
    Last Update:
    See Project
  • 2
    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...
    Downloads: 7 This Week
    Last Update:
    See Project
  • 3
    Synthetic Data Vault (SDV)

    Synthetic Data Vault (SDV)

    Synthetic Data Generation for tabular, relational and time series data

    The Synthetic Data Vault (SDV) is a Synthetic Data Generation ecosystem of libraries that allows users to easily learn single-table, multi-table and timeseries datasets to later on generate new Synthetic Data that has the same format and statistical properties as the original dataset. Synthetic data can then be used to supplement, augment and in some cases replace real data when training Machine Learning models. Additionally, it enables the testing of Machine Learning or other data dependent...
    Downloads: 1 This Week
    Last Update:
    See Project
  • 4
    Lightweight' GAN

    Lightweight' GAN

    Implementation of 'lightweight' GAN, proposed in ICLR 2021

    Implementation of 'lightweight' GAN proposed in ICLR 2021, in Pytorch. The main contribution of the paper is a skip-layer excitation in the generator, paired with autoencoding self-supervised learning in the discriminator. Quoting the one-line summary "converge on single gpu with few hours' training, on 1024 resolution sub-hundred images". Augmentation is essential for Lightweight GAN to work effectively in a low data setting. You can test and see how your images will be augmented before...
    Downloads: 0 This Week
    Last Update:
    See Project
  • Intelligent testing agents | Checksum.ai Icon
    Intelligent testing agents | Checksum.ai

    Checksum generates, runs, and maintains end-to-end tests automatically so your team ships with confidence as code output grows.

    Coding agents write the code. Checksum runs it—continuously testing against real APIs, real data, real edge cases—before it ever reaches production.
    Learn More
  • 5
    GPT-Code UI

    GPT-Code UI

    An open source implementation of OpenAI's ChatGPT Code interpreter

    An open source implementation of OpenAI's ChatGPT Code interpreter. Simply ask the OpenAI model to do something and it will generate & execute the code for you. You can put a .env in the working directory to load the OPENAI_API_KEY environment variable. For Azure OpenAI Services, there are also other configurable variables like deployment name. See .env.azure-example for more information. Note that model selection on the UI is currently not supported for Azure OpenAI Services.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 6
    Coframe

    Coframe

    Coframe brings your UX to life with AI-powered optimization

    Bring your UX to life with AI-powered optimization and personalization. Coframe brings the content of your app or website to life through AI-powered optimization, personalization, and overall self-improvement. It takes minutes to integrate, and the ROI is clear to measure. Your website or app gains self-enhancing abilities with Coframe, learning from real-world performance. It's A/B testing, but with a serious upgrade. Coframe uses the latest in AI to generate copy that is tailored to your...
    Downloads: 0 This Week
    Last Update:
    See Project
  • 7
    AI Atelier

    AI Atelier

    Based on the Disco Diffusion, version of the AI art creation software

    Based on the Disco Diffusion, we have developed a Chinese & English version of the AI art creation software "AI Atelier". We offer both Text-To-Image models (Disco Diffusion and VQGAN+CLIP) and Text-To-Text (GPT-J-6B and GPT-NEOX-20B) as options. Making available complete source code of licensed works and modifications, which include larger works using a licensed work, under the same license. Copyright and license notices must be preserved.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 8
    ML for Trading

    ML for Trading

    Code for machine learning for algorithmic trading, 2nd edition

    On over 800 pages, this revised and expanded 2nd edition demonstrates how ML can add value to algorithmic trading through a broad range of applications. Organized in four parts and 24 chapters, it covers the end-to-end workflow from data sourcing and model development to strategy backtesting and evaluation. Covers key aspects of data sourcing, financial feature engineering, and portfolio management. The design and evaluation of long-short strategies based on a broad range of ML algorithms,...
    Downloads: 9 This Week
    Last Update:
    See Project
  • 9
    TGAN

    TGAN

    Generative adversarial training for generating synthetic tabular data

    ...TGAN has been developed and runs on Python 3.5, 3.6 and 3.7. Also, although it is not strictly required, the usage of a virtualenv is highly recommended in order to avoid interfering with other software installed in the system where TGAN is run. For development, you can use make install-develop instead in order to install all the required dependencies for testing and code listing. In order to be able to sample new synthetic data, TGAN first needs to be fitted to existing data.
    Downloads: 0 This Week
    Last Update:
    See Project
  • Job Evaluation and Talent Management Software Icon
    Job Evaluation and Talent Management Software

    For human resources departments in search of a tool to manage time, expenses, leave, documents, recruitment, and onboarding

    Encompassing Visions (ENCV), industry-leading job evaluation and pay equity software, is the best choice for organizations requiring transparent, comprehensive, and objective Job Evaluation software designed to help them ensure equal pay for work of equal value.
    Learn More
  • 10
    Grenade

    Grenade

    Deep Learning in Haskell

    Grenade is a composable, dependently typed, practical, and fast recurrent neural network library for concise and precise specifications of complex networks in Haskell. Because the types are so rich, there's no specific term level code required to construct this network; although it is of course possible and easy to construct and deconstruct the networks and layers explicitly oneself. Networks in Grenade can be thought of as a heterogeneous list of layers, where their type includes not only...
    Downloads: 0 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next
MongoDB Logo MongoDB