Question: what gets stored in the datasets cache and why is it so huge?
Hi ! As Albert said they can sometimes take more space that expected but we'll fix that soon.

Also, to give more details about caching: computations on a dataset are cached by default so that you don't have to recompute them the next time you run them.

So by default the cache files stay on your disk when you job is finished (so that if you re-execute it, it will be reloaded from the cache).
Feel free to clear your cache after your job has finished, or disable caching using
```python
import datasets

datasets.set_caching_enabled(False)
```
I'm running several training jobs (around 10) with a relatively large dataset (3M samples). The datasets cache reached 178G and it seems really large. What is it stored in there and why is it so large? I don't think I noticed this problem before and seems to be related to the new version of the datasets library. Any insight? Thank you!
Question: what gets stored in the datasets cache and why is it so huge? 
 I'm running several training jobs (around 10) with a relatively large dataset (3M samples). The datasets cache reached 178G and it seems really large. What is it stored in there and why is it so large? I don't think I noticed this problem before and seems to be related to the new version of the datasets library. Any insight? Thank you! 
 Hi ! As Albert said they can sometimes take more space that expected but we'll fix that soon.

Also, to give more details about caching: computations on a dataset are cached by default so that you don't have to recompute them the next time you run them.

So by default the cache files stay on your disk when you job is finished (so that if you re-execute it, it will be reloaded from the cache).
Feel free to clear your cache after your job has finished, or disable caching using
```python
import datasets

datasets.set_caching_enabled(False)
```