|
--- |
|
license: apache-2.0 |
|
task_categories: |
|
- text-classification |
|
language: |
|
- en |
|
pretty_name: section 5 zst datasets |
|
--- |
|
# Hugging Face course section 5 .zst datasets |
|
You can use [these datasets](https://huggingface.co/datasets/mdroth/PubMed-200k-RTC/tree/main/data) for whatever you want (note the [Apache 2.0 license](https://huggingface.co/datasets/mdroth/PubMed-200k-RTC/blob/main/data/Apache_2.0), though) but their primary purpose is to serve as a drop-in replacement for the sub-datasets of [The Pile](https://pile.eleuther.ai/) used in [section 5](https://huggingface.co/learn/nlp-course/chapter5/4?fw=pt#what-is-the-pile) of the [HuggingFace course](https://huggingface.co/learn/nlp-course/chapter5/4?fw=pt#what-is-the-pile). |
|
|
|
## Data sources |
|
- PubMed-200k-RTC:<br>https://www.kaggle.com/datasets/matthewjansen/pubmed-200k-rtc/download?datasetVersionNumber=5 |
|
- LegalText-classification:<br>https://www.kaggle.com/datasets/shivamb/legal-citation-text-classification/download?datasetVersionNumber=1 |
|
|
|
These are Kaggle datasets. So you need to be logged into a [Kaggle account](https://www.kaggle.com/account/login?phase=startSignInTab&returnUrl=%2F) to download them from Kaggle. However, you actually don't need to download (and preprocess) them from Kaggle – you can just use them as shown in the following **Usage** section. |
|
|
|
## Usage |
|
To load a dataset from this repo, run |
|
|
|
```python |
|
import zstandard |
|
from datasets import load_dataset |
|
load_dataset("json", data_files=url, split="train") |
|
``` |
|
|
|
where `url` should be one of the following download links: |
|
- `LegalText-classification_train.jsonl.zst`:<br>https://huggingface.co/datasets/mdroth/PubMed-200k-RTC/resolve/main/data/LegalText-classification_train.jsonl.zst, |
|
- `LegalText-classification_train_min.jsonl.zst`:<br>https://huggingface.co/datasets/mdroth/PubMed-200k-RTC/resolve/main/data/LegalText-classification_train_min.jsonl.zst, |
|
- `PubMed-200k-RTC_train.jsonl.zst`:<br>https://huggingface.co/datasets/mdroth/PubMed-200k-RTC/resolve/main/data/PubMed-200k-RTC_train.jsonl.zst, or |
|
- `PubMed-200k-RTC_train_min.jsonl.zst`:<br>https://huggingface.co/datasets/mdroth/PubMed-200k-RTC/resolve/main/data/PubMed-200k-RTC_train_min.jsonl.zst. |
|
|
|
Example: |
|
|
|
```python |
|
import zstandard |
|
from datasets import load_dataset |
|
url = "https://huggingface.co/datasets/mdroth/PubMed-200k-RTC/resolve/main/data/LegalText-classification_train_min.jsonl.zst" |
|
load_dataset("json", data_files=url, split="train") |
|
``` |
