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IVY download for Windows

Free download IVY Windows app to run online win Wine in Ubuntu online, Fedora online or Debian online

This is the Windows app named IVY whose latest release can be downloaded as Ivyv1.0.0.5sourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.

Download and run online this app named IVY with OnWorks for free.

Follow these instructions in order to run this app:

- 1. Downloaded this application in your PC.

- 2. Enter in our file manager https://www.onworks.net/myfiles.php?username=XXXXX with the username that you want.

- 3. Upload this application in such filemanager.

- 4. Start any OS OnWorks online emulator from this website, but better Windows online emulator.

- 5. From the OnWorks Windows OS you have just started, goto our file manager https://www.onworks.net/myfiles.php?username=XXXXX with the username that you want.

- 6. Download the application and install it.

- 7. Download Wine from your Linux distributions software repositories. Once installed, you can then double-click the app to run them with Wine. You can also try PlayOnLinux, a fancy interface over Wine that will help you install popular Windows programs and games.

Wine is a way to run Windows software on Linux, but with no Windows required. Wine is an open-source Windows compatibility layer that can run Windows programs directly on any Linux desktop. Essentially, Wine is trying to re-implement enough of Windows from scratch so that it can run all those Windows applications without actually needing Windows.

SCREENSHOTS

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IVY


DESCRIPTION

Take any code that you'd like to include. For example, an existing TensorFlow model, and some useful functions from both PyTorch and NumPy libraries. Choose any framework for writing your higher-level pipeline, including data loading, distributed training, analytics, logging, visualization etc. Choose any backend framework which should be used under the hood, for running this entire pipeline. Choose the most appropriate device or combination of devices for your needs. DeepMind releases an awesome model on GitHub, written in JAX. We'll use PerceiverIO as an example. Implement the model in PyTorch yourself, spending time and energy ensuring every detail is correct. Otherwise, wait for a PyTorch version to appear on GitHub, among the many re-implementation attempts that appear (a, b, c, d, e, f). Instantly transpile the JAX model to PyTorch. This creates an identical PyTorch equivalent of the original model.



Features

  • Choose any framework for writing your higher level pipeline
  • Choose any backend framework which should be used under the hood
  • Choose the most appropriate device or combination of devices for your needs
  • Take any code that you'd like to include
  • Add examples
  • Ivy can transpile any function in your library to any target framework


Programming Language

Python


Categories

Frameworks, Machine Learning

This is an application that can also be fetched from https://sourceforge.net/projects/ivy.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.


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