This pull request makes it possible to run your model inside a Docker environment, which makes it easier for other people to run it. We're using an open source tool called Cog to make this process easier.
This also means we can make a web page where other people can try out your model! View it here: https://replicate.com/cszn/scunet. The docker file can be found under the tab ārun model with dockerā.
We have added some examples, but do claim the page so you can own the page, customise the Example gallery as you like, push any future update to the web demo, and we'll feature it on our website and tweet about it too. Moreover, when the page is claimed, it will be automatically linked to the arXiv website as well (under āDemosā)! You can find the 'Claim this model' button on the top of the page ~
In case you're wondering who I am, I'm fromĀ Replicate, where we're trying to make machine learning reproducible. We got frustrated that we couldn't run all the really interesting ML work being done. So, we're going round implementing models we like.Ā š
cszn
commented
2 years ago
Hey @cszn! š
This pull request makes it possible to run your model inside a Docker environment, which makes it easier for other people to run it. We're using an open source tool called Cog to make this process easier.
This also means we can make a web page where other people can try out your model! View it here: https://replicate.com/cszn/scunet. The docker file can be found under the tab ārun model with dockerā.
We have added some examples, but do claim the page so you can own the page, customise the Example gallery as you like, push any future update to the web demo, and we'll feature it on our website and tweet about it too. Moreover, when the page is claimed, it will be automatically linked to the arXiv website as well (under āDemosā)! You can find the 'Claim this model' button on the top of the page ~
In case you're wondering who I am, I'm fromĀ Replicate, where we're trying to make machine learning reproducible. We got frustrated that we couldn't run all the really interesting ML work being done. So, we're going round implementing models we like.Ā š