Showing 3 open source projects for "types"

View related business solutions
  • Build Agents and Models on One Platform Icon
    Build Agents and Models on One Platform

    Everything you need to build production-ready agents and models. Access 200+ Google and third-party AI models and tools.

    Gemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
    Start Free
  • MongoDB Atlas runs apps anywhere Icon
    MongoDB Atlas runs apps anywhere

    Deploy in 115+ regions with the modern database for every enterprise.

    MongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
    Start Free
  • 1
    snacks.nvim

    snacks.nvim

    A collection of QoL plugins for Neovim

    snacks.nvim is a playful and minimal plugin for Neovim that shows little "snack" animations or messages in the command line during idle moments. It adds charm and personality to the editor without being intrusive, appealing to users who enjoy aesthetic feedback in their development environment. snacks.nvim is written in Lua and intended as a lighthearted UX enhancement.
    Downloads: 4 This Week
    Last Update:
    See Project
  • 2
    char-rnn

    char-rnn

    Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN)

    char-rnn is a classic codebase for training multi-layer recurrent neural networks on raw text to build character-level language models that learn to predict the next character in a sequence. It supports common recurrent architectures including vanilla RNNs as well as LSTM and GRU variants, letting users compare behavior and output quality across model types. It is straightforward: you provide a single text file, train the model to minimize next-character prediction loss, then sample from the trained network to generate new text one character at a time in the style of the dataset. The project is designed for experimentation, offering tunable settings for depth, hidden size, dropout, sequence length, and sampling temperature to control creativity and coherence. ...
    Downloads: 0 This Week
    Last Update:
    See Project
  • 3
    Property/configuration mechanism for high-performance C++ applications. Similar to but more flexible than Java properties. Property settings provide type safety, expressive error messages and full-featured expressions. Based on the Lua language.
    Downloads: 0 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next