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Yeah - different projects have different goals and licenses aren't one size fits all. Depending on the project, type of technology, goals, etc.. we will select or even develop the right license that aligns with those goals. Hope this helps :)
Yep - here is the site: https://www.metaconnect.com/en/home
Partner integrations will follow. For now we just have the weights available.
But don't worry, this community moves fast!
It would be interesting to understand if a ~30B Llama-2 model would be interesting and for what reasons.
If you watch the Connect talks, I'll be speaking about this..
thanks for posting this - you can learn more here: https://ai.facebook.com/blog/protein-folding-esmfold-metagen...
Cheers!
It's really awesome to finally see this landed. Congrats to the team and to the PyTorch community!
PyTorch Mobile is a start and is available for iOS and Android. Given folks like PFN and Microsoft are (or will be heavy contributors) i would expect support for more devices to broaden. Have you tried it out yet? No need for a separate set of op semantics or framework.. :) https://pytorch.org/mobile/home/
We have been working with G on TPU support for PyTorch. Have you tried it out? https://github.com/pytorch/xla
Finally the solution to all of your PyTorch citation problems! :)
Yeah, generally a cloud based approach to training models is better than on your mac. AMD folks have been working on RoCM for some time and it works reasonably well for common models but the AMD GPU HW isn't pervasive like Nvidia GPUs in places like AWS.
If you are looking at using Colab for prototyping, you can also try TPUs which are now supported for PyTorch. Here is the link some additional info including some Colab NBs: https://github.com/pytorch/xla
Amazon backing MXNet is pretty awesome and having it be a 'real' open project is great for the community..