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Update parquet files
Browse files- Persian-conversational-dataset.py +0 -100
- README.md +0 -10
- dadrah_dataset.json +0 -0
- dadrah_dataset1-100000_276342.json +0 -3
- dadrah_dataset1-1000_10000.json → default/persian-conversational-dataset-test.parquet +2 -2
- dadrah_dataset1-10000_100000.json → default/persian-conversational-dataset-train.parquet +2 -2
Persian-conversational-dataset.py
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# coding=utf-8
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# persian-conversational-dataset
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"""TODO(empathetic_dialogues): Add a description here."""
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import csv
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import json
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import datasets
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from datasets.tasks import QuestionAnsweringExtractive
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logger = datasets.logging.get_logger(__name__)
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_DESCRIPTION = """\
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persian-conversational-dataset
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"""
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_URL = "https://huggingface.co/datasets/Kamtera/Persian-conversational-dataset/blob/main/"
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_URLS = [
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"dadrah_dataset.json",
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"dadrah_dataset1-1000_10000.json",
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"dadrah_dataset1-10000_100000.json",
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"dadrah_dataset1-100000_276342.json",
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]
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class persianConversation(datasets.GeneratorBasedBuilder):
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# VERSION = datasets.Version("0.1.0")
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def _info(self):
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# TODO(empathetic_dialogues): Specifies the datasets.DatasetInfo object
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return datasets.DatasetInfo(
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# This is the description that will appear on the datasets page.
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description=_DESCRIPTION,
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# datasets.features.FeatureConnectors
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features=datasets.Features(
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{
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"title": datasets.Value("string"),
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"question": datasets.Value("string"),
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"answers": datasets.Sequence(datasets.Value("string")),
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"keywords": datasets.Sequence(datasets.Value("string")),
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# These are the features of your dataset like images, labels ...
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}
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),
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# If there's a common (input, target) tuple from the features,
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# specify them here. They'll be used if as_supervised=True in
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# builder.as_dataset.
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supervised_keys=None,
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)
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def _split_generators(self, dl_manager):
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"""Returns SplitGenerators."""
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# TODO(empathetic_dialogues): Downloads the data and defines the splits
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# dl_manager is a datasets.download.DownloadManager that can be used to
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# download and extract URLs
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downloaded_files = dl_manager.download(_URLS)
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logger.info("| > downloaded files")
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logger.info(downloaded_files)
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return [
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datasets.SplitGenerator(
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name=datasets.Split.TRAIN,
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# These kwargs will be passed to _generate_examples
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gen_kwargs={
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"files": downloaded_files[1:],
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"split_file": "train",
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},
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),
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datasets.SplitGenerator(
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name=datasets.Split.TEST,
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# These kwargs will be passed to _generate_examples
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gen_kwargs={
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"files": downloaded_files[0:1],
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"split_file": "test"
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},
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),
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]
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def _generate_examples(self, files, split_file):
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"""Yields examples."""
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import json
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logger.info("| > generate examples for "+split_file)
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logger.info(files)
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for path in files:
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with open(path, 'r', encoding='utf-8') as fmm:
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data=json.load(fmm)
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for id_, row in enumerate(data):
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title=row[0]
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question=row[1]
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answers=row[2]
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keywords=row[3]
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yield id_, {
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"title": title,
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"question": question,
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"answers": answers,
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"keywords": keywords,
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}
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README.md
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---
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license: apache-2.0
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task_categories:
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- conversational
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- text-generation
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language:
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- fa
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pretty_name: persianConversation
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---
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persianConversation
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dadrah_dataset.json
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dadrah_dataset1-100000_276342.json
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version https://git-lfs.github.com/spec/v1
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oid sha256:1899baa9c9ec851411892b866c11f58437cc624d82d96cb2fcc94ff2358bbbed
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size 530182133
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dadrah_dataset1-1000_10000.json → default/persian-conversational-dataset-test.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:f0d7ed11dc7185835edf23ea2d8370a76a0da73bcd311649a073795285e5da11
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size 755507
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dadrah_dataset1-10000_100000.json → default/persian-conversational-dataset-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 sha256:813c9d35fe7987fb5aef5e2234ed0572e5ed98ddc3a12f91252df616f24a239c
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size 143700175
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