datasets. We will go over this part pretty quickly. Since the focus of this tutorial is on training, you should refer
to the 🤗 Datasets documentation or the preprocessing tutorial for
more information.
First, we can use the load_dataset function to download and cache the dataset:
```python
from datasets import load_dataset
raw_datasets = load_dataset("imdb")
```
This works like the from_pretrained method we saw for the models and tokenizers (except the cache directory is
~/.cache/huggingface/dataset by default).
The raw_datasets object is a dictionary with three keys: "train", "test" and "unsupervised"
(which correspond to the three splits of that dataset). We will use the "train" split for training and the
"test" split for validation.
To preprocess our data, we will need a tokenizer:
```python
