You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Mounting MyDrive is typically helpful, but in comparison to reading and writing files within the rest of the content directories otherwise, it is very slow. I have my own personal set of images to train - these files are tiny and about 30kb each and unpacking the archive should be no sweat for any consumer PC, but unfortunately trying to unpack them through Colab's 7z is very slow, possibly due to rate limits. It's enough to go out and get some breakfast. It's not worth it trying to upload these images one by one through GDrive either or to move back and forth, so I believe it may be a benefit to provide the option to process the images through Dataset and then train them outside, downloading any results and needed (aside from output results).
Glancing at the first cell of the Dataset Maker, it seems like just preventing GDrive from connecting sets the directory to ~/Loras regardless, but it would still be useful to have a visual and still link GDrive if needed for other purposes.
(It should be noted that storage-based formats like .tar probably work best with Colab.)
The text was updated successfully, but these errors were encountered:
Could you explain why the following doesn't fit your use case?: You can upload a zip file to your drive, and use the dedicated cell to extract it to a path in the colab storage.
So far we've only tested with Pony and not the other models so I cant speak to those. But with Pony, we're getting 2-3 minutes saved. I think it depends on the hardware or timing you get. The colab is a little changed because part of what makes it faster is unzipping on the go, so it is currently setup at the beginning.
I don't think @hollowstrawberry would want that many changes though. So, these changes will probably not be implemented and I don't think i would want to support an actual fork, so think of it as a temporary beta test.
Mounting MyDrive is typically helpful, but in comparison to reading and writing files within the rest of the content directories otherwise, it is very slow. I have my own personal set of images to train - these files are tiny and about 30kb each and unpacking the archive should be no sweat for any consumer PC, but unfortunately trying to unpack them through Colab's 7z is very slow, possibly due to rate limits. It's enough to go out and get some breakfast. It's not worth it trying to upload these images one by one through GDrive either or to move back and forth, so I believe it may be a benefit to provide the option to process the images through Dataset and then train them outside, downloading any results and needed (aside from output results).
Glancing at the first cell of the Dataset Maker, it seems like just preventing GDrive from connecting sets the directory to ~/Loras regardless, but it would still be useful to have a visual and still link GDrive if needed for other purposes.
(It should be noted that storage-based formats like .tar probably work best with Colab.)
The text was updated successfully, but these errors were encountered: