Datasets:
Tasks:
Text Generation
Formats:
parquet
Sub-tasks:
language-modeling
Languages:
Danish
Size:
10M - 100M
ArXiv:
DOI:
License:
Kenneth Enevoldsen
commited on
format
Browse files
data/memo/create.py
CHANGED
@@ -96,9 +96,9 @@ def load_memo(repo_path: Path) -> pd.DataFrame:
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text_without_metadata = [t for t in text_df_fileames if t not in metadata_filenames]
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assert
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)
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# merge texts with metadata
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merged_df = pd.merge(
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text_without_metadata = [t for t in text_df_fileames if t not in metadata_filenames]
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+
assert (
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len(text_without_metadata) == 0
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), f"Some texts in the repository do not have metadata: {text_without_metadata}"
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# merge texts with metadata
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merged_df = pd.merge(
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src/dynaword/update_descriptive_statistics.py
CHANGED
@@ -100,7 +100,6 @@ def update_dataset(
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sheet.body = sheet.add_descriptive_stats(descriptive_stats=desc_stats)
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sheet.body = sheet.add_sample_and_description()
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-
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if dataset_name == "default":
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logger.info("Updating Overview table")
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overview_table = create_overview_table_str()
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sheet.body = sheet.add_descriptive_stats(descriptive_stats=desc_stats)
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sheet.body = sheet.add_sample_and_description()
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if dataset_name == "default":
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logger.info("Updating Overview table")
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overview_table = create_overview_table_str()
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src/tests/test_quality/test_short_texts.py
CHANGED
@@ -16,6 +16,6 @@ def test_no_one_word_documents(dataset_name: str):
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one_word_docs = ds.filter(lambda x: x["token_count"] <= 1)
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assert
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)
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one_word_docs = ds.filter(lambda x: x["token_count"] <= 1)
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assert (
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len(one_word_docs) == 0
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), f"Found {len(one_word_docs)} one-word documents in dataset '{dataset_name}'"
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