Datasets:
yelp
/

Modalities:
Text
Formats:
parquet
Languages:
English
ArXiv:
Libraries:
Datasets
pandas
License:
albertvillanova HF staff commited on
Commit
c1f9ee9
1 Parent(s): 18a3aad

Convert dataset to Parquet (#4)

Browse files

- Convert dataset to Parquet (bfd4401da2a18714a29e1c60738b0f03e6f563d9)
- Delete loading script (ac93e45d283c1b883519f47a951adfdbc2f2232f)
- Delete legacy dataset_infos.json (c4efa06f630e42303cf333dd4d6d4a36b53a0d2e)

README.md CHANGED
@@ -20,6 +20,7 @@ task_ids:
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  pretty_name: YelpReviewFull
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  license_details: yelp-licence
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  dataset_info:
 
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  features:
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  - name: label
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  dtype:
@@ -32,7 +33,6 @@ dataset_info:
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  '4': 5 stars
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  - name: text
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  dtype: string
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- config_name: yelp_review_full
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  splits:
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  - name: train
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  num_bytes: 483811554
@@ -40,8 +40,16 @@ dataset_info:
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  - name: test
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  num_bytes: 37271188
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  num_examples: 50000
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- download_size: 196146755
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  dataset_size: 521082742
 
 
 
 
 
 
 
 
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  train-eval-index:
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  - config: yelp_review_full
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  task: text-classification
 
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  pretty_name: YelpReviewFull
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  license_details: yelp-licence
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  dataset_info:
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+ config_name: yelp_review_full
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  features:
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  - name: label
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  dtype:
 
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  '4': 5 stars
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  - name: text
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  dtype: string
 
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  splits:
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  - name: train
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  num_bytes: 483811554
 
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  - name: test
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  num_bytes: 37271188
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  num_examples: 50000
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+ download_size: 322952369
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  dataset_size: 521082742
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+ configs:
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+ - config_name: yelp_review_full
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+ data_files:
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+ - split: train
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+ path: yelp_review_full/train-*
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+ - split: test
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+ path: yelp_review_full/test-*
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+ default: true
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  train-eval-index:
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  - config: yelp_review_full
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  task: text-classification
dataset_infos.json DELETED
@@ -1 +0,0 @@
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- {"yelp_review_full": {"description": "The Yelp reviews dataset consists of reviews from Yelp. It is extracted from the Yelp Dataset Challenge 2015 data.\nThe Yelp reviews full star dataset is constructed by Xiang Zhang ([email protected]) from the above dataset.\nIt is first used as a text classification benchmark in the following paper: Xiang Zhang, Junbo Zhao, Yann LeCun.\nCharacter-level Convolutional Networks for Text Classification. Advances in Neural Information Processing Systems 28 (NIPS 2015).\n", "citation": "@inproceedings{zhang2015character,\n title={Character-level convolutional networks for text classification},\n author={Zhang, Xiang and Zhao, Junbo and LeCun, Yann},\n booktitle={Advances in neural information processing systems},\n pages={649--657},\n year={2015}\n}\n", "homepage": "https://www.yelp.com/dataset", "license": "https://s3-media3.fl.yelpcdn.com/assets/srv0/engineering_pages/bea5c1e92bf3/assets/vendor/yelp-dataset-agreement.pdf", "features": {"label": {"num_classes": 5, "names": ["1 star", "2 star", "3 stars", "4 stars", "5 stars"], "id": null, "_type": "ClassLabel"}, "text": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": [{"task": "text-classification", "text_column": "text", "label_column": "label"}], "builder_name": "yelp_review_full", "config_name": "yelp_review_full", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 483811554, "num_examples": 650000, "dataset_name": "yelp_review_full"}, "test": {"name": "test", "num_bytes": 37271188, "num_examples": 50000, "dataset_name": "yelp_review_full"}}, "download_checksums": {"https://s3.amazonaws.com/fast-ai-nlp/yelp_review_full_csv.tgz": {"num_bytes": 196146755, "checksum": "56006b0a17a370f1e366504b1f2c3e3754e4a3dda17d3e718a885c552869a559"}}, "download_size": 196146755, "post_processing_size": null, "dataset_size": 521082742, "size_in_bytes": 717229497}}
 
 
yelp_review_full.py DELETED
@@ -1,124 +0,0 @@
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- # coding=utf-8
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- # Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
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- #
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- # Licensed under the Apache License, Version 2.0 (the "License");
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- # you may not use this file except in compliance with the License.
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- # You may obtain a copy of the License at
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- #
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- # http://www.apache.org/licenses/LICENSE-2.0
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- #
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- # Unless required by applicable law or agreed to in writing, software
11
- # distributed under the License is distributed on an "AS IS" BASIS,
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- # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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- # See the License for the specific language governing permissions and
14
- # limitations under the License.
15
- """The Yelp Review Full dataset for text classification."""
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-
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-
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- import csv
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-
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- import datasets
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- from datasets.tasks import TextClassification
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-
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-
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- _CITATION = """\
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- @inproceedings{zhang2015character,
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- title={Character-level convolutional networks for text classification},
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- author={Zhang, Xiang and Zhao, Junbo and LeCun, Yann},
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- booktitle={Advances in neural information processing systems},
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- pages={649--657},
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- year={2015}
31
- }
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- """
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-
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- _DESCRIPTION = """\
35
- The Yelp reviews dataset consists of reviews from Yelp. It is extracted from the Yelp Dataset Challenge 2015 data.
36
- The Yelp reviews full star dataset is constructed by Xiang Zhang ([email protected]) from the above dataset.
37
- It is first used as a text classification benchmark in the following paper: Xiang Zhang, Junbo Zhao, Yann LeCun.
38
- Character-level Convolutional Networks for Text Classification. Advances in Neural Information Processing Systems 28 (NIPS 2015).
39
- """
40
-
41
- _HOMEPAGE = "https://www.yelp.com/dataset"
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-
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- _LICENSE = "https://s3-media3.fl.yelpcdn.com/assets/srv0/engineering_pages/bea5c1e92bf3/assets/vendor/yelp-dataset-agreement.pdf"
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-
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- _URLs = {
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- "yelp_review_full": "https://s3.amazonaws.com/fast-ai-nlp/yelp_review_full_csv.tgz",
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- }
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-
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-
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- class YelpReviewFullConfig(datasets.BuilderConfig):
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- """BuilderConfig for YelpReviewFull."""
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-
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- def __init__(self, **kwargs):
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- """BuilderConfig for YelpReviewFull.
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-
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- Args:
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- **kwargs: keyword arguments forwarded to super.
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- """
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- super(YelpReviewFullConfig, self).__init__(**kwargs)
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-
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-
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- class YelpReviewFull(datasets.GeneratorBasedBuilder):
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- """Yelp Review Full Star Dataset 2015."""
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-
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- VERSION = datasets.Version("1.0.0")
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-
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- BUILDER_CONFIGS = [
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- YelpReviewFullConfig(
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- name="yelp_review_full", version=VERSION, description="Yelp Review Full Star Dataset 2015"
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- ),
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- ]
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-
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- def _info(self):
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- features = datasets.Features(
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- {
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- "label": datasets.features.ClassLabel(
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- names=[
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- "1 star",
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- "2 star",
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- "3 stars",
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- "4 stars",
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- "5 stars",
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- ]
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- ),
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- "text": datasets.Value("string"),
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- }
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- )
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- return datasets.DatasetInfo(
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- description=_DESCRIPTION,
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- features=features,
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- supervised_keys=None,
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- homepage=_HOMEPAGE,
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- license=_LICENSE,
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- citation=_CITATION,
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- task_templates=[TextClassification(text_column="text", label_column="label")],
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- )
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-
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- def _split_generators(self, dl_manager):
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- """Returns SplitGenerators."""
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- my_urls = _URLs[self.config.name]
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- archive = dl_manager.download(my_urls)
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- return [
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- datasets.SplitGenerator(
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- name=datasets.Split.TRAIN,
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- gen_kwargs={"filepath": "yelp_review_full_csv/train.csv", "files": dl_manager.iter_archive(archive)},
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- ),
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- datasets.SplitGenerator(
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- name=datasets.Split.TEST,
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- gen_kwargs={"filepath": "yelp_review_full_csv/test.csv", "files": dl_manager.iter_archive(archive)},
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- ),
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- ]
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-
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- def _generate_examples(self, filepath, files):
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- """Yields examples."""
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- for path, f in files:
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- if path == filepath:
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- csvfile = (line.decode("utf-8") for line in f)
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- data = csv.reader(csvfile, delimiter=",", quoting=csv.QUOTE_NONNUMERIC)
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- for id_, row in enumerate(data):
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- yield id_, {
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- "text": row[1],
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- "label": int(row[0]) - 1,
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- }
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- break
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
yelp_review_full/test-00000-of-00001.parquet ADDED
@@ -0,0 +1,3 @@
 
 
 
 
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:bf06d5969bff93ecd4a6d4b330643761ce108b42e9b8a894cf82c9df02a08540
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+ size 23515519
yelp_review_full/train-00000-of-00001.parquet ADDED
@@ -0,0 +1,3 @@
 
 
 
 
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:da3ca3dcc52b1e2e44195b53668610d645a59010a985dd45aa12e1109cd44601
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+ size 299436850