Update parquet files

imdb_pt.py

@@ -1,86 +0,0 @@
-"""IMDB movie reviews dataset translated to Portuguese."""
-
-import csv
-
-import datasets
-from datasets.tasks import TextClassification
-
-_DESCRIPTION = """\
-Large Movie Review Dataset.
-This is a dataset for binary sentiment classification containing substantially \
-more data than previous benchmark datasets. We provide a set of 25,000 highly \
-polar movie reviews for training, and 25,000 for testing. There is additional \
-unlabeled data for use as well.\
-"""
-
-_CITATION = """\
-@InProceedings{maas-EtAl:2011:ACL-HLT2011,
-  author    = {Maas, Andrew L.  and  Daly, Raymond E.  and  Pham, Peter T.  and  Huang, Dan  and  Ng, Andrew Y.  and  Potts, Christopher},
-  title     = {Learning Word Vectors for Sentiment Analysis},
-  booktitle = {Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies},
-  month     = {June},
-  year      = {2011},
-  address   = {Portland, Oregon, USA},
-  publisher = {Association for Computational Linguistics},
-  pages     = {142--150},
-  url       = {http://www.aclweb.org/anthology/P11-1015}
-}
-"""
-
-_DOWNLOAD_URL = "https://huggingface.co/datasets/maritaca-ai/imdb_pt/resolve/main"
-
-class IMDBReviewsConfig(datasets.BuilderConfig):
-    """BuilderConfig for IMDBReviews."""
-
-    def __init__(self, **kwargs):
-        """BuilderConfig for IMDBReviews.
-        Args:
-          **kwargs: keyword arguments forwarded to super.
-        """
-        super().__init__(version=datasets.Version("1.0.0", ""), **kwargs)
-
-class Imdb(datasets.GeneratorBasedBuilder):
-    """IMDB movie reviews dataset translated to Portuguese."""
-
-    BUILDER_CONFIGS = [
-        IMDBReviewsConfig(
-            name="plain_text",
-            description="Plain text",
-        )
-    ]
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {"text": datasets.Value("string"), "label": datasets.features.ClassLabel(names=["negativo", "posisivo"])}
-            ),
-            supervised_keys=None,
-            homepage="http://ai.stanford.edu/~amaas/data/sentiment/",
-            citation=_CITATION,
-            task_templates=[TextClassification(text_column="text", label_column="label")],
-        )
-
-    def _split_generators(self, dl_manager):
-        train_path = dl_manager.download_and_extract(f"{_DOWNLOAD_URL}/train.csv")
-        test_path = dl_manager.download_and_extract(f"{_DOWNLOAD_URL}/test.csv")
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN, gen_kwargs={"filepath": train_path, "split": "train"}
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST, gen_kwargs={"filepath": test_path, "split": "test"}
-            ),
-        ]
-
-    def _generate_examples(self, filepath, split):
-        """Generate aclImdb examples."""
-        with open(filepath, encoding="utf-8") as csv_file:
-          csv_reader = csv.reader(
-              csv_file, quotechar='"', delimiter=",", quoting=csv.QUOTE_ALL, skipinitialspace=True
-          )
-          for id_, row in enumerate(csv_reader):
-                  if id_ == 0:
-                    continue
-                  text, label = row
-                  yield id_, {"text": text, "label": label}

test.csv → plain_text/imdb_pt-test.parquet

@@ -1,3 +1,3 @@
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-size 32799465
+oid sha256:8d4cd262e652734b1ab93e063051d1dca65cb42d0437c7ec7f06939c726d5f27
+size 20279716

train.csv → plain_text/imdb_pt-train.parquet

@@ -1,3 +1,3 @@
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-oid sha256:2fcdc5f90812858d4bd9ce8d3107583c60fcdef6ab071f649058c016e2c2966d
-size 33342600
+oid sha256:aa94b8de669ec7c9e8924a99b41cdff454e075b77746d0ac6ecdcd00d65aefb9
+size 20607461