This is the Windows app named Phenaki - Pytorch whose latest release can be downloaded as 0.4.1sourcecode.zip. It can be run online in the free hosting provider OnWorks for workstations.
Download and run online this app named Phenaki - Pytorch 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
Ad
Phenaki - Pytorch
DESCRIPTION
Implementation of Phenaki Video, which uses Mask GIT to produce text-guided videos of up to 2 minutes in length, in Pytorch. It will also combine another technique involving a token critic for potentially even better generations. A new paper suggests that instead of relying on the predicted probabilities of each token as a measure of confidence, one can train an extra critic to decide what to iteratively mask during sampling. This repository will also endeavor to allow the researcher to train on text-to-image and then text-to-video. Similarly, for unconditional training, the researcher should be able to first train on images and then fine tune on video.
Features
- Implementation of Phenaki Video
- Uses Mask GIT to produce text guided videos
- Videos of up to 2 minutes in length
- Combines techniques involving a token critic for potentially even better generations
- You can optionally train this critic for potentially better generations
- This repository will also endeavor to allow the researcher to train on text-to-image and then text-to-video
Programming Language
Python
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/phenaki-pytorch.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.
