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The dataset generation failed
Error code:   DatasetGenerationError
Exception:    UnicodeDecodeError
Message:      'utf-8' codec can't decode byte 0xff in position 0: invalid start byte
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1854, in _prepare_split_single
                  for _, table in generator:
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 686, in wrapped
                  for item in generator(*args, **kwargs):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/text/text.py", line 73, in _generate_tables
                  batch = f.read(self.config.chunksize)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/utils/file_utils.py", line 826, in read_with_retries
                  out = read(*args, **kwargs)
                File "/usr/local/lib/python3.9/codecs.py", line 322, in decode
                  (result, consumed) = self._buffer_decode(data, self.errors, final)
              UnicodeDecodeError: 'utf-8' codec can't decode byte 0xff in position 0: invalid start byte
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1412, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 988, in stream_convert_to_parquet
                  builder._prepare_split(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1741, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1897, in _prepare_split_single
                  raise DatasetGenerationError("An error occurred while generating the dataset") from e
              datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset

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=========================================================
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===================================================
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End of preview.

This ~8.5k dataset is a curated selection of posts with more than 2,000 likes on pixiv between 2024/07/01 and 2024-09/25.

Collection date: 2024-09-29 Tags collected: '女の子', 'users入り', '女の子', 'ふともも', '太もも', '魅惑の太もも', '魅惑のふともも', 'へそ', 'おへそ', 'おっぱい', '魅惑の谷間', '極上の乳', '巨乳', '着衣巨乳', '崩壊:スターレイル', 'ブルーアーカイブ', 'バーチャルYouTuber', '原神 Tags excluded: '3DCG','筋肉娘','男の娘','女装男子','腐向け','BL','Koikatsu','Koikatsu!','コイカツ','コイカツ!','ふたなり','メス男子', 'むちむち','ムチムチ', 'ぽっちゃり', '熟女','AI','AI生成','AI-generated','AIイラスト' Criteria for removal when curating: Duplicate images, Western cartoon drawings, excessively fat or skinny figures, cartoons, CG, or other non-aesthetic things.

⚠️ Caution: This json is information about each 'post'. Since there may be images of multiple topics within one post, using the Tags part of the json as is may produce bad results.

json format:

  [
      {
          "title": "title",
          "type": "illust",
          "tags": [
              "tag1",
              "tag2",
              "tag3"
          ],
          "user": {
              "name": "name",
              "account": "account"
          },
          "total_bookmarks": bookmarks_count
      }
  ]

non_artist_image_list.txt stores image IDs for which the artist's name or address is not stored in danbooru when creating the dataset.

Disclaimer

No Warranties: The creators of the dataset provide it "as is" and make no warranties regarding the dataset's quality, reliability, or fitness for any particular purpose.

Indemnification: Users agree to indemnify and hold harmless the creators against any claims, damages, or liabilities arising from their use of the dataset.

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