cache_dir parameter for load_from_disk ?
Indeed reading the data shouldn't increase the VM's disk. Not sure what google colab does under the hood for that to happen
**Is your feature request related to a problem? Please describe.**
When using Google Colab big datasets can be an issue, as they won't fit on the VM's disk. Therefore mounting google drive could be a possible solution. Unfortunatly when loading my own dataset by using the _load_from_disk_ function, the data gets cached to the VM's disk:

`
from datasets import load_from_disk

myPreprocessedData = load_from_disk("/content/gdrive/MyDrive/ASR_data/myPreprocessedData")

`
I know that chaching on google drive could slow down learning. But at least it would run.

**Describe the solution you'd like**
Add cache_Dir parameter to the load_from_disk function.

**Describe alternatives you've considered**
It looks like you could write a custom loading script for the load_dataset function. But this seems to be much too complex for my use case. Is there perhaps a template here that uses the load_from_disk function?

cache_dir parameter for load_from_disk ? 
 **Is your feature request related to a problem? Please describe.**
When using Google Colab big datasets can be an issue, as they won't fit on the VM's disk. Therefore mounting google drive could be a possible solution. Unfortunatly when loading my own dataset by using the _load_from_disk_ function, the data gets cached to the VM's disk:

`
from datasets import load_from_disk

myPreprocessedData = load_from_disk("/content/gdrive/MyDrive/ASR_data/myPreprocessedData")

`
I know that chaching on google drive could slow down learning. But at least it would run.

**Describe the solution you'd like**
Add cache_Dir parameter to the load_from_disk function.

**Describe alternatives you've considered**
It looks like you could write a custom loading script for the load_dataset function. But this seems to be much too complex for my use case. Is there perhaps a template here that uses the load_from_disk function?
 
 Indeed reading the data shouldn't increase the VM's disk. Not sure what google colab does under the hood for that to happen