Showing 2 open source projects for "decoder"

View related business solutions
  • 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.
    Try Retool free
  • Easily Host LLMs and Web Apps on Cloud Run Icon
    Easily Host LLMs and Web Apps on Cloud Run

    Run everything from popular models with on-demand NVIDIA L4 GPUs to web apps without infrastructure management.

    Run frontend and backend services, batch jobs, host LLMs, and queue processing workloads without the need to manage infrastructure. Cloud Run gives you on-demand GPU access for hosting LLMs and running real-time AI—with 5-second cold starts and automatic scale-to-zero so you only pay for actual usage. New customers get $300 in free credit to start.
    Try Cloud Run Free
  • 1
    Pytorch-toolbelt

    Pytorch-toolbelt

    PyTorch extensions for fast R&D prototyping and Kaggle farming

    ...Extras for Catalyst library (Visualization of batch predictions, additional metrics). By design, both encoder and decoder produces a list of tensors, from fine (high-resolution, indexed 0) to coarse (low-resolution) feature maps. Access to all intermediate feature maps is beneficial if you want to apply deep supervision losses on them or encoder-decoder of object detection task.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 2
    DETR

    DETR

    End-to-end object detection with transformers

    ...Unlike traditional computer vision techniques, DETR approaches object detection as a direct set prediction problem. It consists of a set-based global loss, which forces unique predictions via bipartite matching, and a Transformer encoder-decoder architecture. Given a fixed small set of learned object queries, DETR reasons about the relations of the objects and the global image context to directly output the final set of predictions in parallel. Due to this parallel nature, DETR is very fast and efficient.
    Downloads: 0 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next
MongoDB Logo MongoDB
Gen AI apps are built with MongoDB Atlas
Atlas offers built-in vector search and global availability across 125+ regions. Start building AI apps faster, all in one place.
Try Free →