How to use it: 

```
from datasets import load_dataset

remote_dataset = load_dataset("VanessaSchenkel/translation-en-pt", field="data")

remote_dataset
```

Output:
```
DatasetDict({
    train: Dataset({
        features: ['id', 'translation'],
        num_rows: 260482
    })
})
```

Exemple: 
```
remote_dataset["train"][5]
```

Output:
```
{'id': '5',
 'translation': {'english': 'I have to go to sleep.',
  'portuguese': 'Tenho de dormir.'}}
 ```
task_categories:translation annotations_creators:found language_creators:found multilinguality:translation size_categories:100K<n<1M source_datasets:original language:en language:pt license:afl-3.0 region:us
{"annotations_creators": ["found"], "language_creators": ["found"], "language": ["en", "pt"], "license": ["afl-3.0"], "multilinguality": ["translation"], "size_categories": ["100K<n<1M"], "source_datasets": ["original"], "task_categories": ["translation"], "task_ids": [], "pretty_name": "VanessaSchenkel/translation-en-pt", "tags": []}
TAGS
#task_categories-translation #annotations_creators-found #language_creators-found #multilinguality-translation #size_categories-100K<n<1M #source_datasets-original #language-English #language-Portuguese #license-afl-3.0 #region-us 

How to use it: 



Output:


Exemple: 


Output:

TAGS
#task_categories-translation #annotations_creators-found #language_creators-found #multilinguality-translation #size_categories-100K<n<1M #source_datasets-original #language-English #language-Portuguese #license-afl-3.0 #region-us 
