# Contructing a dataset with categorical labels
**URL:**
**Author:**  [@david-waterworth](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Fu%2Fdavid-waterworth)%5C
**Post date:** [July 17, 2023, 2:02am UTC](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fcontructing-a-dataset-with-categorical-labels%2F47024%2F1 "2023-07-17T02:02:54Z")
All of the `dataset` examples appear to hard-code the list of labels, i.e. [ag\_news](https://huggingface.co/datasets/ag_news/blob/main/ag_news.py)
```python
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
"text": datasets.Value("string"),
"label": datasets.features.ClassLabel(names=["World", "Sports", "Business", "Sci/Tech"]),
}
),
homepage="http://groups.di.unipi.it/~gulli/AG_corpus_of_news_articles.html",
citation=_CITATION,
task_templates=[TextClassification(text_column="text", label_column="label")],
)
```
I’d like to load my labels from a file (i.e. either use the `names_file` argument of ClassLabel or load directly read a json file and construct the `names` argument.
The issue I’m having is the ` _info(self)` method doesn’t give me access to a `download_manager` so I cannot get the path to names\_file in the cache.
I don’t want to hard code my labels, I have different variants with different labels and I want to include a metadata file that includes the labels per variant along with additional identifiers.
Note I’ve also posted to SO [python - Creating a Huggingface Dataset with categorical class labels from a file - Stack Overflow](https://stackoverflow.com/questions/76701199/creating-a-huggingface-dataset-with-categorical-class-labels-from-a-file)
---
**Author:**  [@mariosasko](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Fu%2Fmariosasko)%5C
**Post date:** [July 17, 2023, 2:36pm UTC](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fcontructing-a-dataset-with-categorical-labels%2F47024%2F2 "2023-07-17T14:36:18Z")
I think the simplest solution is to define a (Python) module that contains the lists of labels and then import this module and compute the labels.
`names_file` is a concept that comes from Tensorflow Datasets (this project started as a fork of TFDS)
---
**Author:**  [@david-waterworth](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Fu%2Fdavid-waterworth)%5C
**Post date:** [July 18, 2023, 3:50am UTC](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fcontructing-a-dataset-with-categorical-labels%2F47024%2F3 "2023-07-18T03:50:19Z")
Yeah I’ve been stepping through the `load_dataset` source and confirmed `self._info()` is called before the cache dir is setup so looks like this might be the best option. ☹