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474f20c
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Upload id_multilabel_hs.py with huggingface_hub

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  1. id_multilabel_hs.py +12 -12
id_multilabel_hs.py CHANGED
@@ -4,9 +4,9 @@ from typing import Dict, List, Tuple
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  import datasets
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  import pandas as pd
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- from nusacrowd.utils import schemas
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- from nusacrowd.utils.configs import NusantaraConfig
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- from nusacrowd.utils.constants import Tasks
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  _CITATION = """\
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  @inproceedings{ibrohim-budi-2019-multi,
@@ -53,28 +53,28 @@ _URLS = {
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  }
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  _SUPPORTED_TASKS = [Tasks.ASPECT_BASED_SENTIMENT_ANALYSIS]
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  _SOURCE_VERSION = "1.0.0"
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- _NUSANTARA_VERSION = "1.0.0"
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  class IdAbusive(datasets.GeneratorBasedBuilder):
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  """The ID_MULTILABEL_HS dataset is multi-label hate speech and abusive language detection in Indonesian tweets"""
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  SOURCE_VERSION = datasets.Version(_SOURCE_VERSION)
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- NUSANTARA_VERSION = datasets.Version(_NUSANTARA_VERSION)
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  BUILDER_CONFIGS = [
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- NusantaraConfig(
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  name="id_multilabel_hs_source",
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  version=SOURCE_VERSION,
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  description="ID Multilabel HS source schema",
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  schema="source",
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  subset_id="id_multilabel_hs",
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  ),
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- NusantaraConfig(
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- name="id_multilabel_hs_nusantara_text_multi",
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- version=NUSANTARA_VERSION,
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  description="ID Multilabel HS Nusantara schema",
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- schema="nusantara_text_multi",
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  subset_id="id_multilabel_hs",
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  ),
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  ]
@@ -98,7 +98,7 @@ class IdAbusive(datasets.GeneratorBasedBuilder):
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  "HS_Moderate": datasets.Value("bool"),
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  "HS_Strong": datasets.Value("bool"),
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  })
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- elif self.config.schema == "nusantara_text_multi":
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  features = schemas.text_multi_features([0, 1])
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  return datasets.DatasetInfo(
@@ -142,7 +142,7 @@ class IdAbusive(datasets.GeneratorBasedBuilder):
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  ex[label] = getattr(row, label)
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  yield row.id, ex
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- elif self.config.schema == "nusantara_text_multi":
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  for row in df.itertuples():
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  ex = {
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  "id": str(row.id),
 
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  import datasets
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  import pandas as pd
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+ from seacrowd.utils import schemas
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+ from seacrowd.utils.configs import SEACrowdConfig
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+ from seacrowd.utils.constants import Tasks
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  _CITATION = """\
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  @inproceedings{ibrohim-budi-2019-multi,
 
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  }
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  _SUPPORTED_TASKS = [Tasks.ASPECT_BASED_SENTIMENT_ANALYSIS]
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  _SOURCE_VERSION = "1.0.0"
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+ _SEACROWD_VERSION = "2024.06.20"
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  class IdAbusive(datasets.GeneratorBasedBuilder):
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  """The ID_MULTILABEL_HS dataset is multi-label hate speech and abusive language detection in Indonesian tweets"""
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  SOURCE_VERSION = datasets.Version(_SOURCE_VERSION)
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+ SEACROWD_VERSION = datasets.Version(_SEACROWD_VERSION)
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  BUILDER_CONFIGS = [
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+ SEACrowdConfig(
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  name="id_multilabel_hs_source",
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  version=SOURCE_VERSION,
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  description="ID Multilabel HS source schema",
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  schema="source",
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  subset_id="id_multilabel_hs",
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  ),
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+ SEACrowdConfig(
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+ name="id_multilabel_hs_seacrowd_text_multi",
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+ version=SEACROWD_VERSION,
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  description="ID Multilabel HS Nusantara schema",
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+ schema="seacrowd_text_multi",
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  subset_id="id_multilabel_hs",
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  ),
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  ]
 
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  "HS_Moderate": datasets.Value("bool"),
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  "HS_Strong": datasets.Value("bool"),
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  })
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+ elif self.config.schema == "seacrowd_text_multi":
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  features = schemas.text_multi_features([0, 1])
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  return datasets.DatasetInfo(
 
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  ex[label] = getattr(row, label)
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  yield row.id, ex
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+ elif self.config.schema == "seacrowd_text_multi":
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  for row in df.itertuples():
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  ex = {
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  "id": str(row.id),