Showing 2 open source projects for "code block"

View related business solutions
  • 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
  • Run Any Workload on Compute Engine VMs Icon
    Run Any Workload on Compute Engine VMs

    From dev environments to AI training, choose preset or custom VMs with 1–96 vCPUs and industry-leading 99.95% uptime SLA.

    Compute Engine delivers high-performance virtual machines for web apps, databases, containers, and AI workloads. Choose from general-purpose, compute-optimized, or GPU/TPU-accelerated machine types—or build custom VMs to match your exact specs. With live migration and automatic failover, your workloads stay online. New customers get $300 in free credits.
    Try Compute Engine
  • 1
    Aniseed

    Aniseed

    Neovim configuration and plugins in Fennel (Lisp compiled to Lua)

    ...Allowing you to easily write plugins or configurations in a Clojure-like Lisp with great runtime performance. For interactive evaluation, you need to install Conjure as well. It’ll allow you to send portions of your code off for evaluation as well as see the results in an interactive log buffer. Aniseed ships with a set of module macros that make interactive evaluation not only possible but rich and intuitive. You should read:h aniseed to learn the details but it’s worth mentioning that you opt-in by starting your file with a (module …​) block, you then export values from your module with the (def…​) macros.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 2
    ResNeXt

    ResNeXt

    Implementation of a classification framework

    ...Instead of simply increasing depth or width, ResNeXt introduces a new dimension called cardinality, which refers to the number of parallel transformation paths (i.e. the number of “branches”) that are aggregated together. Each branch is a small transformation (e.g. bottleneck block) and their outputs are summed—this enables richer representation without excessive parameter blowup. The design is modular and homogeneous, making it relatively easy to scale (by tuning cardinality, width, depth) and adopt in existing residual frameworks. The official repository offers a Torch (Lua) implementation with code for training, evaluation, and pretrained models on ImageNet. ...
    Downloads: 0 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next
MongoDB Logo MongoDB