or TensorFlow notebook.
Load WNUT 17 dataset
Load the WNUT 17 dataset from the 🤗 Datasets library:
```python
from datasets import load_dataset
wnut = load_dataset("wnut_17")
```
A quick look at the dataset shows the labels associated with each word in the sentence:
```python
wnut["train"][0]
{'id': '0',
 'ner_tags': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 8, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0],
 'tokens': ['@paulwalk', 'It', "'s", 'the', 'view', 'from', 'where', 'I', "'m", 'living', 'for', 'two', 'weeks', '.', 'Empire', 'State', 'Building', '=', 'ESB', '.', 'Pretty', 'bad', 'storm', 'here', 'last', 'evening', '.']
}
```
View the specific NER tags by:
```python
label_list = wnut["train"].features[f"ner_tags"].feature.names
label_list
[
    "O",
    "B-corporation",
    "I-corporation",
    "B-creative-work",
