NonMatchingSplitsSizesError when loading blog_authorship_corpus
> I'm getting this same issue when loading the `imdb` corpus via `dataset = load_dataset("imdb")`. When I try `ignore_verifications=True`, no examples are read into the `train` portion of the dataset.

When the checksums don't match, it may mean that the file you downloaded is corrupted. In this case you can try to load the dataset again `load_dataset("imdb", download_mode="force_redownload")`

Also I just checked on my side and it worked fine:

```python
from datasets import load_dataset

dataset = load_dataset("imdb")
print(len(dataset["train"]))
# 25000
```

Let me know if redownloading fixes your issue @EmilyAlsentzer .
If not, feel free to open a separate issue.
Getting this error when i run `nlp.load_dataset('blog_authorship_corpus')`. 

```
raise NonMatchingSplitsSizesError(str(bad_splits))
nlp.utils.info_utils.NonMatchingSplitsSizesError: [{'expected': SplitInfo(name='train', 
num_bytes=610252351, num_examples=532812, dataset_name='blog_authorship_corpus'), 
'recorded': SplitInfo(name='train', num_bytes=616473500, num_examples=536323, 
dataset_name='blog_authorship_corpus')}, {'expected': SplitInfo(name='validation', 
num_bytes=37500394, num_examples=31277, dataset_name='blog_authorship_corpus'), 
'recorded': SplitInfo(name='validation', num_bytes=30786661, num_examples=27766, 
dataset_name='blog_authorship_corpus')}]
```

Upon checking it seems like there is a disparity between the information in `datasets/blog_authorship_corpus/dataset_infos.json` and what was downloaded. Although I can get away with this by passing `ignore_verifications=True` in `load_dataset`, I'm thinking doing so might give problems later on.
NonMatchingSplitsSizesError when loading blog_authorship_corpus 
 Getting this error when i run `nlp.load_dataset('blog_authorship_corpus')`. 

```
raise NonMatchingSplitsSizesError(str(bad_splits))
nlp.utils.info_utils.NonMatchingSplitsSizesError: [{'expected': SplitInfo(name='train', 
num_bytes=610252351, num_examples=532812, dataset_name='blog_authorship_corpus'), 
'recorded': SplitInfo(name='train', num_bytes=616473500, num_examples=536323, 
dataset_name='blog_authorship_corpus')}, {'expected': SplitInfo(name='validation', 
num_bytes=37500394, num_examples=31277, dataset_name='blog_authorship_corpus'), 
'recorded': SplitInfo(name='validation', num_bytes=30786661, num_examples=27766, 
dataset_name='blog_authorship_corpus')}]
```

Upon checking it seems like there is a disparity between the information in `datasets/blog_authorship_corpus/dataset_infos.json` and what was downloaded. Although I can get away with this by passing `ignore_verifications=True` in `load_dataset`, I'm thinking doing so might give problems later on. 
 > I'm getting this same issue when loading the `imdb` corpus via `dataset = load_dataset("imdb")`. When I try `ignore_verifications=True`, no examples are read into the `train` portion of the dataset.

When the checksums don't match, it may mean that the file you downloaded is corrupted. In this case you can try to load the dataset again `load_dataset("imdb", download_mode="force_redownload")`

Also I just checked on my side and it worked fine:

```python
from datasets import load_dataset

dataset = load_dataset("imdb")
print(len(dataset["train"]))
# 25000
```

Let me know if redownloading fixes your issue @EmilyAlsentzer .
If not, feel free to open a separate issue.