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Update parquet files
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.gitattributes
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*.7z filter=lfs diff=lfs merge=lfs -text
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saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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klue-re-v1.1_dev.json filter=lfs diff=lfs merge=lfs -text
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klue-re-v1.1_train.json filter=lfs diff=lfs merge=lfs -text
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klue-re-v1.1_dev.json → KLUE Relation Extraction/klue-re-train.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:da3fcb0001c700a21abe2ad7de1176aa624a03a21008c82929f2a734faa88a3d
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size 6652833
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klue-re-v1.1_train.json → KLUE Relation Extraction/klue-re-validation.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:d7483fe529658d33e374205c1d399a8f84d46a0b87f26062178e63e96f3b5a70
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size 1543139
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klue-re.py
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import json
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import pandas as pd
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import datasets
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logger = datasets.logging.get_logger(__name__)
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_DESCRIPTION = """\
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Klue Relation Extraction Data
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"""
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_URL = "https://huggingface.co/datasets/LeverageX/klue-re/resolve/main/"
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_URLS = {
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"train_data": _URL + "klue-re-v1.1_train.json",
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"validation_data": _URL + "klue-re-v1.1_dev.json",
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}
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class KoreanNewspaper(datasets.GeneratorBasedBuilder):
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BUILDER_CONFIGS = [
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datasets.BuilderConfig(
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name="KLUE Relation Extraction",
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version=datasets.Version("1.0.0", ""),
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description="For LeverageX Project",
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),
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]
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def _info(self):
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return datasets.DatasetInfo(
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description=_DESCRIPTION,
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features=datasets.Features(
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{
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"guid": datasets.Value("string"),
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"label": datasets.Value("string"),
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"object_entity":
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{
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"word": datasets.Value("string"),
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"start_idx": datasets.Value("int32"),
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"end_idx": datasets.Value("int32"),
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"type": datasets.Value("string"),
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},
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"sentence": datasets.Value("string"),
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"source": datasets.Value("string"),
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"subject_entity":
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{
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"word": datasets.Value("string"),
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"start_idx": datasets.Value("int32"),
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"end_idx": datasets.Value("int32"),
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"type": datasets.Value("string"),
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}
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}
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),
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# No default supervised_keys (as we have to pass both question
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# and context as input).
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supervised_keys=None,
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homepage="https://klue-benchmark.com/tasks/70/overview/description",
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)
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def _split_generators(self, dl_manager):
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downloaded_files = dl_manager.download_and_extract(_URLS)
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return [
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datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train_data"]}),
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datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["validation_data"]}),
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]
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def _generate_examples(self, filepath):
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"""This function returns the examples in the raw (text) form."""
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logger.info("generating examples from = %s", filepath)
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key = 0
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with open(filepath, encoding="utf-8") as f :
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data = json.load(f)
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for info in data :
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guid = info['guid']
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label = info['label']
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object_entity = info['object_entity']
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subject_entity = info['subject_entity']
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source = info['source']
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sentence = info['sentence']
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yield key, {
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"guid" : guid,
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"label" : label,
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"object_entity" : object_entity,
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"subject_entity" : subject_entity,
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"source" : source,
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"sentence" : sentence,
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}
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key += 1
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