Deploy Libraries

36 Components & Libraries

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Deploy Libraries

OpenSource self-service infrastructure solution that defines and manages the complete lifecycle of resources used and provisioned into a cloud! It is a terraform UI with rest api for terraform and OpenTofu automation

SLD helps to accelerate deployment, weighting and making IaaC reusable, generating dynamic forms and maintaining different variables in each environment with the same code. With SLD you can schedule…

🪄 Turns your machine learning code into microservices with web API, interactive GUI, and more.

Instantly turn your Python functions into production-ready microservices. Deploy and access your services via HTTP API or interactive UI. Seamlessly export your services into portable, shareable, and…

Scramjet Transform Hub (STH) is a runtime supervisor that can run data processing programs called Sequences and manage local resources on any Linux server, Docker on small edge servers, and even large-scale Kubernetes clusters in the cloud or datacenters. It connects to Scramjet Spaces in Scramjet Cloud Platform.

Scramjet Transform Hub is a cool way to run programs on your computer or in the cloud. It's easy to use, and it supports lots of different types of programs. The Hub is the heart of Scramjet Cloud Pl…

Using the GPT3 Language model, I create a web application that generates convincing looking emails and then sends them via Gmail. The user interacts with a frontend made with Streamlit

DaisyKit is an easy AI toolkit with face mask detection, pose detection, background matting, barcode detection, face recognition and more. - with NCNN, OpenCV, Python wrappers

Install packages from Terminal For Windows, Visual Studio 2019 + Git Bash is recommended. Clone the source code: Build Daisykit: Run face detection example: Build Daisykit: Run face detection example…

The fastest way to deploy AI apps and services on any infra. Unobtrusive, debuggable, PyTorch-like APIs.

Runhouse is built to do four things: The above env list is a shorthand, but you can create quite elaborate envs (even quite a bit more elaborate than the example below). Local folders are sent (rsync…

A fast, easy-to-use, production-ready inference server for computer vision supporting deployment of many popular model architectures and fine-tuned models.

You can run Inference on an edge device like an NVIDIA Jetson, or on cloud computing platforms like AWS, GCP, and Azure. Currently, the stream interface only supports object detection Check out Infer…

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