--- 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:
https://www.kaggle.com/datasets/matthewjansen/pubmed-200k-rtc/download?datasetVersionNumber=5 - LegalText-classification:
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`:
https://huggingface.co/datasets/mdroth/PubMed-200k-RTC/resolve/main/data/LegalText-classification_train.jsonl.zst, - `LegalText-classification_train_min.jsonl.zst`:
https://huggingface.co/datasets/mdroth/PubMed-200k-RTC/resolve/main/data/LegalText-classification_train_min.jsonl.zst, - `PubMed-200k-RTC_train.jsonl.zst`:
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`:
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") ```