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Thanks @jeremy I’ll use Gradient for now for the course, then think about choosing one way or another, I have a project up on the Core machine that I’m plugging away at.
Just a note: I’m checking out Gradient and I was running the lesson1-pets notebook, and it seemed to get stuck on this line: help(untar_data). The kernel was still saying it was running after several minutes, even after the progress bar got to 100%. Not sure what caused that exactly, but I just wanted to report that if you hit that situation, I was able to just hit the stop button, run the cell again, and proceed through the rest of the notebook.
We are seeing that as well. Seems to just be taking a while to untar the image in the /storage persistent data directory. If it looks frozen after a few minutes you can try to start the notebook again.
Hello! I already have a VM with fastaiv07 (which i want to maintain), which will be the steps to create a 2nd environment where to install the last version of fastai?
I was in the same situation with a paperspace P4000 set up for the previous course. When I tried running the first notebook I realised it used the CPU because it took such a long time, when I saw on Jeremy’s notebook it only took 30 seconds for one epoch. It turned out that you have to upgrade the CUDA version to 9.2 (I had 9.1). It was a little bit messy, I mainly followed the instructions here: https://medium.com/@abhiksingla10/installing-cuda-9-2-and-cudnn-7-1-on-ubuntu-16-04-d194cee27cba .
In summary you have to install/upgrade three things:
Nvidia drivers: NVIDIA Drivers 396.54 worked for me with CUDA 9.2
Hi Dan, I´ve been using paperspace for the last six month´s and I ´d like to keep using paperspace for this new fastai v3 course. I´ve tried many times to set a new machine, but I´m having lots of problems every time I create a new machine. I wish I could have a step by step tutorial that could work for fastai v1.0.11, which is the more stable version today. Otherwise, I believe myself and many old customers will end up changing to google and AWS … Thanks