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BioNLP2021.py

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-import os
-
-import datasets
-import pandas as pd
-
-_CITATION = None
-
-_DESCRIPTION = """\
-MEDIQA @ NAACL-BioNLP 2021 -- Task 2: Multi-answer summarization
-https://sites.google.com/view/mediqa2021
-Biomedical Summarization Data
-The MEDIQA-AnS Dataset could be used for training.
-"""
-_HOMEPAGE = "https://github.com/abachaa/MEDIQA2021/tree/main/Task2"
-_LICENSE = None
-_DATA_URL = "https://huggingface.co/datasets/nbtpj/BioNLP2021/resolve/main/{split_name}.csv"
-           
-_SPLIT = ['train_mul', 'train_sig', 'validate', 'test']
-
-
-class BioNLP2021(datasets.BuilderConfig):
-    """BuilderConfig for GLUE."""
-
-    def __init__(self, data_url, **kwargs):
-        """BuilderConfig for BioNLP2021MAS
-        Args:
-          data_url: `string`, url to the dataset (word or raw level)
-          **kwargs: keyword arguments forwarded to super.
-        """
-        super(BioNLP2021, self).__init__(
-            version=datasets.Version(
-                "1.0.0",
-            ),
-            **kwargs,
-        )
-        self.data_url = data_url
-
-
-class Loader(datasets.GeneratorBasedBuilder):
-    VERSION = datasets.Version("0.1.0")
-    BUILDER_CONFIGS = [BioNLP2021(name='BioNLP2021', data_url=_DATA_URL)]
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            # This is the description that will appear on the datasets page.
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "text": datasets.Value("string"),
-                    "question": datasets.Value("string"),
-                    "key": datasets.Value("string"),
-                    "summ_abs": datasets.Value("string"),
-                    "summ_ext": datasets.Value("string"),
-                    # These are the features of your dataset like images, labels ...
-                    # key,question,sum_abs,sum_ext,rating,section,article,text
-
-                }
-            ),
-            # If there's a common (input, target) tuple from the features,
-            # specify them here. They'll be used if as_supervised=True in
-            # builder.as_dataset.
-            supervised_keys=None,
-            homepage=_HOMEPAGE,
-            license=_LICENSE,
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        rs = []
-        for split in _SPLIT:
-          file= dl_manager.download_and_extract(_DATA_URL.format(split_name=split))
-          rs.append(
-              datasets.SplitGenerator(
-                name=split,
-                gen_kwargs={"data_file": file, "split": split },
-            ))
-        
-
-        return rs
-
-
-    def _generate_examples(self, data_file, split):
-        """Yields examples."""
-        with open(data_file, encoding="utf-8") as f:
-            f = pd.read_csv(f).to_dict('records')
-            for idx, row in enumerate(f):
-                yield idx, row

BioNLP2021/bio_nlp2021-test.parquet

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BioNLP2021/bio_nlp2021-train_mul.parquet

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BioNLP2021/bio_nlp2021-train_sig.parquet

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BioNLP2021/bio_nlp2021-validate.parquet

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