Update parquet files

README.md

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----
-annotations_creators:
-- no-annotation
-language:
-- zh
-license:
-- apache-2.0
-pretty_name: CSL
-size_categories:
-- 100K<n<1M
-source_datasets:
-- extended|csl
-tags: []
-task_categories:
-- text-retrieval
-task_ids:
-- document-retrieval
----
-
-# Dataset Card for CSL
-
-## Dataset Description
-
-CSL is the Chinese Scientific Literature Dataset.
-
-- **Paper:** https://aclanthology.org/2022.coling-1.344
-- **Repository:** https://github.com/ydli-ai/CSL
-
-### Dataset Summary
-
-The dataset contains titles, abstracts, keywords of papers written in Chinese from several academic fields.
-
-### Languages
-
- - Chinese
-
-## Dataset Structure
-
-### Data Instances
-
-| Split           | Documents |
-|-----------------|----------:|
-| `csl`           |      396k |
-
-### Data Fields
-
- - `doc_id`: unique identifier for this document
- - `title`: title of the paper
- - `abstract`: abstract of the paper
- - `keywords`: keywords associated with the paper
- - `category`: English translaction of the broad category (e.g., Engineering)
- - `category_zho`: the broad category of the paper
- - `discipline`: English translation of the academic discipline (e.g., Agricultural Engineering)
- - `discipline_zho`: academic discipline of the paper
-
-## Dataset Usage
-
-Using 🤗 Datasets:
-
-```python
-from datasets import load_dataset
-
-dataset = load_dataset('neuclir/csl')['csl']
-```
-
-## License & Citation
-
-This dataset is based off the [Chinese Scientific Literature Dataset](https://github.com/ydli-ai/CSL) under Apache 2.0.
-The primay change is the addition of English translactions of the category and discipline descriptions by a native speaker.
-
-If you use this data, please cite:
-
-```
-@inproceedings{li-etal-2022-csl,
-    title = "{CSL}: A Large-scale {C}hinese Scientific Literature Dataset",
-    author = "Li, Yudong  and
-      Zhang, Yuqing  and
-      Zhao, Zhe  and
-      Shen, Linlin  and
-      Liu, Weijie  and
-      Mao, Weiquan  and
-      Zhang, Hui",
-    booktitle = "Proceedings of the 29th International Conference on Computational Linguistics",
-    month = oct,
-    year = "2022",
-    address = "Gyeongju, Republic of Korea",
-    publisher = "International Committee on Computational Linguistics",
-    url = "https://aclanthology.org/2022.coling-1.344",
-    pages = "3917--3923",
-}
-```

csl.py

@@ -1,40 +0,0 @@
-import gzip
-import json
-import datasets
-
-_URLS = {
-  "csl": "https://huggingface.co/datasets/neuclir/csl/resolve/main/data/csl.jsonl.gz"
-}
-
-class Csl(datasets.GeneratorBasedBuilder):
-    VERSION = datasets.Version("1.0.0")
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            features=datasets.Features({
-              "doc_id": datasets.Value("string"),
-              "title": datasets.Value("string"),
-              "abstract": datasets.Value("string"),
-              "keywords": datasets.Sequence(feature=datasets.Value("string"), length=-1),
-              "category": datasets.Value("string"),
-              "category_zho": datasets.Value("string"),
-              "discipline": datasets.Value("string"),
-              "discipline_zho": datasets.Value("string"),
-            }),
-        )
-
-    def _split_generators(self, dl_manager):
-        paths = dl_manager.download(_URLS)
-        return [
-            datasets.SplitGenerator(
-                name='csl',
-                gen_kwargs={
-                    "filepath": paths['csl'],
-                })
-        ]
-
-    def _generate_examples(self, filepath):
-        with gzip.open(filepath) as f:
-            for key, row in enumerate(f):
-                data = json.loads(row)
-                yield key, data

data/csl.jsonl.gz → default/csl-csl.parquet

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