Problems after upgrading to 2.6.1
Hi! I can't reproduce the error following these steps. Can you please provide a reproducible example? I faced the same issue:

### Repro
```
!pip install datasets==2.6.1
import datasets as Dataset
dataset = Dataset.from_pandas(dataframe)
dataset.save_to_disk(local)

!pip install datasets==2.5.2
import datasets as Dataset
dataset = Dataset.load_from_disk(local)
```

 @Lokiiiiii And what are the contents of the "dataframe" in your example? I bumped into the issue too. @Lokiiiiii thanks for steps. I "solved" if for now by `pip install datasets>=2.6.1` everywhere. Hi all, 
I experienced the same issue. 
Please note that the pull request is related to the IMDB example provided in the doc, and is a fix for that, in that context, to make sure that people can follow the doc example and have a working system. 
It does not provide a fix for Datasets itself. 
### Describe the bug

Loading a dataset_dict from disk with `load_from_disk` is now creating a `KeyError "length"` that was not occurring in v2.5.2.

Context: 
- Each individual dataset in the dict is created with `Dataset.from_pandas` 
- The dataset_dict is create from a dict of `Dataset`s, e.g., `DatasetDict({"train": train_ds, "validation": val_ds})
- The pandas dataframe, besides text columns, has a column with a dictionary inside and potentially different keys in each row. Correctly the `Dataset.from_pandas` function adds `key: None` to all dictionaries in each row so that the schema can be correctly inferred.

### Steps to reproduce the bug

Steps to reproduce:

- Upgrade to datasets==2.6.1
- Create a dataset from pandas dataframe with `Dataset.from_pandas`
- Create a dataset_dict from a dict of `Dataset`s, e.g., `DatasetDict({"train": train_ds, "validation": val_ds})
- Save to disk with the `save` function

### Expected behavior

Same as in v2.5.2, that is load from disk without errors

### Environment info

- `datasets` version: 2.6.1
- Platform: Linux-5.4.209-129.367.amzn2int.x86_64-x86_64-with-glibc2.26
- Python version: 3.9.13
- PyArrow version: 9.0.0
- Pandas version: 1.5.1