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1 Parent(s): b22ff63

add 2021_21 snapshot

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  1. 2021_21/dedup/oscar-000000000001.json.gz +3 -0
  2. 2021_21/dedup/oscar-000000000002.json.gz +3 -0
  3. 2021_21/dedup/oscar-000000000003.json.gz +3 -0
  4. 2021_21/dedup/oscar-000000000004.json.gz +3 -0
  5. 2021_21/dedup/oscar-000000000005.json.gz +3 -0
  6. 2021_21/dedup/oscar-000000000006.json.gz +3 -0
  7. 2021_21/dedup/oscar-000000000007.json.gz +3 -0
  8. 2021_21/dedup/oscar-000000000008.json.gz +3 -0
  9. 2021_21/dedup/oscar-000000000009.json.gz +3 -0
  10. 2021_21/dedup/oscar-000000000010.json.gz +3 -0
  11. 2021_21/dedup/oscar-000000000011.json.gz +3 -0
  12. 2021_21/dedup/oscar-000000000012.json.gz +3 -0
  13. 2021_21/dedup/oscar-000000000013.json.gz +3 -0
  14. 2021_21/dedup/oscar-000000000014.json.gz +3 -0
  15. 2021_21/dedup/oscar-000000000015.json.gz +3 -0
  16. 2021_21/dedup/oscar-000000000016.json.gz +3 -0
  17. 2021_21/dedup/oscar-000000000017.json.gz +3 -0
  18. 2021_21/dedup/oscar-000000000018.json.gz +3 -0
  19. 2021_21/dedup/oscar-000000000019.json.gz +3 -0
  20. 2021_21/dedup/oscar-000000000020.json.gz +3 -0
  21. 2021_21/dedup/oscar-000000000021.json.gz +3 -0
  22. 2021_21/dedup/oscar-000000000022.json.gz +3 -0
  23. 2021_21/dedup/oscar-000000000023.json.gz +3 -0
  24. 2021_21/dedup/oscar-000000000024.json.gz +3 -0
  25. 2021_21/dedup/oscar-000000000025.json.gz +3 -0
  26. 2021_21/dedup/oscar-000000000026.json.gz +3 -0
  27. 2021_21/dedup/oscar-000000000027.json.gz +3 -0
  28. 2021_21/dedup/oscar-000000000028.json.gz +3 -0
  29. 2021_21/dedup/oscar-000000000029.json.gz +3 -0
  30. 2021_21/dedup/oscar-000000000030.json.gz +3 -0
  31. 2021_21/dedup/oscar-000000000031.json.gz +3 -0
  32. 2021_21/dedup/oscar-000000000032.json.gz +3 -0
  33. 2021_21/dedup/oscar-000000000033.json.gz +3 -0
  34. 2021_21/dedup/oscar-000000000034.json.gz +3 -0
  35. 2021_21/dedup/oscar-000000000035.json.gz +3 -0
  36. 2021_21/dedup/oscar-000000000036.json.gz +3 -0
  37. 2021_21/dedup/oscar-000000000037.json.gz +3 -0
  38. 2021_21/dedup/oscar_2021_21_dedup.py +107 -0
  39. 2021_21/neardup/neardup_clean.py +107 -0
  40. 2021_21/neardup/oscar-neardup-000000000001.json.gz +3 -0
  41. 2021_21/neardup/oscar-neardup-000000000002.json.gz +3 -0
  42. 2021_21/neardup/oscar-neardup-000000000003.json.gz +3 -0
  43. 2021_21/neardup/oscar-neardup-000000000004.json.gz +3 -0
  44. 2021_21/neardup/oscar-neardup-000000000005.json.gz +3 -0
  45. 2021_21/neardup/oscar-neardup-000000000006.json.gz +3 -0
  46. 2021_21/neardup/oscar-neardup-000000000007.json.gz +3 -0
  47. 2021_21/neardup/oscar-neardup-000000000008.json.gz +3 -0
  48. 2021_21/neardup/oscar-neardup-000000000009.json.gz +3 -0
  49. 2021_21/neardup/oscar-neardup-000000000010.json.gz +3 -0
  50. 2021_21/neardup/oscar-neardup-000000000011.json.gz +3 -0
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2021_21/dedup/oscar_2021_21_dedup.py ADDED
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1
+ # coding=utf-8
2
+ # Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
3
+ #
4
+ # Licensed under the Apache License, Version 2.0 (the "License");
5
+ # you may not use this file except in compliance with the License.
6
+ # You may obtain a copy of the License at
7
+ #
8
+ # http://www.apache.org/licenses/LICENSE-2.0
9
+ #
10
+ # Unless required by applicable law or agreed to in writing, software
11
+ # distributed under the License is distributed on an "AS IS" BASIS,
12
+ # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13
+ # See the License for the specific language governing permissions and
14
+ # limitations under the License.
15
+ """Cleaned Indonesian split of the mC4 corpus."""
16
+ import json
17
+ import glob
18
+ import gzip
19
+ import textwrap
20
+ import datasets
21
+ logger = datasets.logging.get_logger(__name__)
22
+
23
+ file = sorted(glob.glob('/data/oscar_2021_21_dedup/data/*'))
24
+ _CITATION = """
25
+ @article{JMLR:v21:20-074,
26
+ author = {Colin Raffel and Noam Shazeer and Adam Roberts and Katherine Lee and Sharan Narang and Michael Matena and Yanqi Zhou and Wei Li and Peter J. Liu},
27
+ title = {Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer},
28
+ journal = {Journal of Machine Learning Research},
29
+ year = {2020},
30
+ volume = {21},
31
+ number = {140},
32
+ pages = {1-67},
33
+ url = {http://jmlr.org/papers/v21/20-074.html}
34
+ }
35
+ """
36
+ _DESCRIPTION = """\
37
+ A thoroughly cleaned version of the Italian portion of the multilingual
38
+ colossal, cleaned version of Common Crawl's web crawl corpus (mC4) by AllenAI.
39
+ Based on Common Crawl dataset: "https://commoncrawl.org".
40
+ This is the processed version of Google's mC4 dataset by AllenAI, with further cleaning
41
+ detailed in the repository README file.
42
+ """
43
+ _HOMEPAGE = "https://github.com/allenai/allennlp/discussions/5056"
44
+ _LICENSE = "Open Data Commons Attribution License (ODC-By) v1.0"
45
+ _BASE_URL = "https://huggingface.co/datasets/munggok/mc4-id/resolve/main/mc4-id-filter/c4-id{split_suffix}.tfrecord-{index:05d}-of-{n_shards:05d}.json.gz"
46
+ _CONFIGS = {
47
+ "tiny": {"train": 100, "validation": 1},
48
+ "small": {"train": 250, "validation": 2},
49
+ "medium": {"train": 500, "validation": 4},
50
+ "large": {"train": 750, "validation": 6},
51
+ "full": {"train": 1016, "validation": 8}
52
+ }
53
+ class OscarConfig(datasets.BuilderConfig):
54
+ """BuilderConfig for the Clean mC4 Italian."""
55
+ def __init__(self, **kwargs):
56
+ """BuilderConfig for Clean mC4 Italian.
57
+ Args:
58
+ **kwargs: keyword arguments forwarded to super.
59
+ """
60
+ super().__init__(**kwargs)
61
+ class Oscar(datasets.GeneratorBasedBuilder):
62
+ """mC4, a colossal, cleaned version of Common Crawl's web crawl corpus."""
63
+ BUILDER_CONFIGS = [
64
+ OscarConfig(
65
+ name="full",
66
+ version=datasets.Version("1.0.0"),
67
+ description=textwrap.dedent(
68
+ f"""\
69
+ The full cleaned version of the Italian portion of the multilingual C4 corpus.
70
+ Estimated size of compressed files: 103GB
71
+ """
72
+ )
73
+ )
74
+ ]
75
+ def _info(self):
76
+ return datasets.DatasetInfo(
77
+ description=_DESCRIPTION,
78
+ features=datasets.Features(
79
+ {
80
+ "text": datasets.Value("string"),
81
+ "url": datasets.Value("string"),
82
+ "timestamp": datasets.Value("string"),
83
+ "meta": datasets.Value("string"),
84
+ }
85
+ ),
86
+ supervised_keys=None,
87
+ homepage=_HOMEPAGE,
88
+ license=_LICENSE,
89
+ citation=_CITATION,
90
+ )
91
+ def _split_generators(self, dl_manager):
92
+ data_urls = {}
93
+ train_downloaded_files = file
94
+ return [
95
+ datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepaths": train_downloaded_files}),
96
+ ]
97
+ def _generate_examples(self, filepaths):
98
+ """This function returns the examples in the raw (text) form by iterating on all the files."""
99
+ id_ = 0
100
+ for filepath in filepaths:
101
+ logger.info(f"Generating examples from {filepath}")
102
+ with gzip.open(open(filepath, "rb"), "rt", encoding="utf-8") as f:
103
+ for line in f:
104
+ if line:
105
+ example = json.loads(line)
106
+ yield id_, {'text':example['text'],'url':example['url'],'timestamp':example['timestamp'],'meta': example['meta']}
107
+ id_ += 1
2021_21/neardup/neardup_clean.py ADDED
@@ -0,0 +1,107 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # coding=utf-8
2
+ # Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
3
+ #
4
+ # Licensed under the Apache License, Version 2.0 (the "License");
5
+ # you may not use this file except in compliance with the License.
6
+ # You may obtain a copy of the License at
7
+ #
8
+ # http://www.apache.org/licenses/LICENSE-2.0
9
+ #
10
+ # Unless required by applicable law or agreed to in writing, software
11
+ # distributed under the License is distributed on an "AS IS" BASIS,
12
+ # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13
+ # See the License for the specific language governing permissions and
14
+ # limitations under the License.
15
+ """Cleaned Indonesian split of the mC4 corpus."""
16
+ import json
17
+ import glob
18
+ import gzip
19
+ import textwrap
20
+ import datasets
21
+ logger = datasets.logging.get_logger(__name__)
22
+
23
+ file = sorted(glob.glob('/data/oscar_id/2021_21/neardup/*.gz'))
24
+ _CITATION = """
25
+ @article{JMLR:v21:20-074,
26
+ author = {Colin Raffel and Noam Shazeer and Adam Roberts and Katherine Lee and Sharan Narang and Michael Matena and Yanqi Zhou and Wei Li and Peter J. Liu},
27
+ title = {Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer},
28
+ journal = {Journal of Machine Learning Research},
29
+ year = {2020},
30
+ volume = {21},
31
+ number = {140},
32
+ pages = {1-67},
33
+ url = {http://jmlr.org/papers/v21/20-074.html}
34
+ }
35
+ """
36
+ _DESCRIPTION = """\
37
+ A thoroughly cleaned version of the Italian portion of the multilingual
38
+ colossal, cleaned version of Common Crawl's web crawl corpus (mC4) by AllenAI.
39
+ Based on Common Crawl dataset: "https://commoncrawl.org".
40
+ This is the processed version of Google's mC4 dataset by AllenAI, with further cleaning
41
+ detailed in the repository README file.
42
+ """
43
+ _HOMEPAGE = "https://github.com/allenai/allennlp/discussions/5056"
44
+ _LICENSE = "Open Data Commons Attribution License (ODC-By) v1.0"
45
+ _BASE_URL = "https://huggingface.co/datasets/munggok/mc4-id/resolve/main/mc4-id-filter/c4-id{split_suffix}.tfrecord-{index:05d}-of-{n_shards:05d}.json.gz"
46
+ _CONFIGS = {
47
+ "tiny": {"train": 100, "validation": 1},
48
+ "small": {"train": 250, "validation": 2},
49
+ "medium": {"train": 500, "validation": 4},
50
+ "large": {"train": 750, "validation": 6},
51
+ "full": {"train": 1016, "validation": 8}
52
+ }
53
+ class OscarConfig(datasets.BuilderConfig):
54
+ """BuilderConfig for the Clean mC4 Italian."""
55
+ def __init__(self, **kwargs):
56
+ """BuilderConfig for Clean mC4 Italian.
57
+ Args:
58
+ **kwargs: keyword arguments forwarded to super.
59
+ """
60
+ super().__init__(**kwargs)
61
+ class Oscar(datasets.GeneratorBasedBuilder):
62
+ """mC4, a colossal, cleaned version of Common Crawl's web crawl corpus."""
63
+ BUILDER_CONFIGS = [
64
+ OscarConfig(
65
+ name="full",
66
+ version=datasets.Version("1.0.0"),
67
+ description=textwrap.dedent(
68
+ f"""\
69
+ The full cleaned version of the Italian portion of the multilingual C4 corpus.
70
+ Estimated size of compressed files: 103GB
71
+ """
72
+ )
73
+ )
74
+ ]
75
+ def _info(self):
76
+ return datasets.DatasetInfo(
77
+ description=_DESCRIPTION,
78
+ features=datasets.Features(
79
+ {
80
+ "text": datasets.Value("string"),
81
+ "url": datasets.Value("string"),
82
+ "timestamp": datasets.Value("string"),
83
+ "meta": datasets.Value("string"),
84
+ }
85
+ ),
86
+ supervised_keys=None,
87
+ homepage=_HOMEPAGE,
88
+ license=_LICENSE,
89
+ citation=_CITATION,
90
+ )
91
+ def _split_generators(self, dl_manager):
92
+ data_urls = {}
93
+ train_downloaded_files = file
94
+ return [
95
+ datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepaths": train_downloaded_files}),
96
+ ]
97
+ def _generate_examples(self, filepaths):
98
+ """This function returns the examples in the raw (text) form by iterating on all the files."""
99
+ id_ = 0
100
+ for filepath in filepaths:
101
+ logger.info(f"Generating examples from {filepath}")
102
+ with gzip.open(open(filepath, "rb"), "rt", encoding="utf-8") as f:
103
+ for line in f:
104
+ if line:
105
+ example = json.loads(line)
106
+ yield id_, {'text':example['text'],'url':example['url'],'timestamp':example['timestamp'],'meta': example['meta']}
107
+ id_ += 1
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