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  1. README.md +20 -5
README.md CHANGED
@@ -159,29 +159,44 @@ TODO: Add comment about larger and noisier sets being better for training.
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  ### Data Instances
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  ```
 
 
 
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  DatasetDict({
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  test: Dataset({
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  features: ['lang', 'sent1', 'sent2', 'annot_score', 'gem_id'],
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- num_rows: 1047
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  })
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  validation: Dataset({
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  features: ['lang', 'sent1', 'sent2', 'annot_score', 'gem_id'],
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- num_rows: 1013
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  })
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  test.full: Dataset({
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  features: ['lang', 'sent1', 'sent2', 'annot_score', 'gem_id'],
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- num_rows: 1586
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  })
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  validation.full: Dataset({
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  features: ['lang', 'sent1', 'sent2', 'annot_score', 'gem_id'],
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- num_rows: 1582
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  })
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  train: Dataset({
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  features: ['lang', 'sent1', 'sent2', 'annot_score', 'gem_id'],
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- num_rows: 590000
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  })
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  })
 
 
 
 
 
 
 
 
 
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  ```
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  ### Data Fields
 
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  ### Data Instances
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+ As a concrete example, loading the English data with a 95% quality of
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+ the train split produces the following:
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+
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  ```
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+ >>> data = load_dataset("GEM/opusparcus", lang="en", quality=95)
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+
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+ >>> data
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  DatasetDict({
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  test: Dataset({
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  features: ['lang', 'sent1', 'sent2', 'annot_score', 'gem_id'],
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+ num_rows: 982
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  })
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  validation: Dataset({
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  features: ['lang', 'sent1', 'sent2', 'annot_score', 'gem_id'],
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+ num_rows: 1015
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  })
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  test.full: Dataset({
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  features: ['lang', 'sent1', 'sent2', 'annot_score', 'gem_id'],
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+ num_rows: 1445
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  })
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  validation.full: Dataset({
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  features: ['lang', 'sent1', 'sent2', 'annot_score', 'gem_id'],
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+ num_rows: 1455
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  })
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  train: Dataset({
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  features: ['lang', 'sent1', 'sent2', 'annot_score', 'gem_id'],
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+ num_rows: 1000000
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  })
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  })
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+
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+ >>> data["test"][0]
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+ {'annot_score': 4.0, 'gem_id': 'gem-opusparcus-test-1587', 'lang': 'en', 'sent1': "I haven 't been contacted by anybody .", 'sent2': "Nobody 's contacted me ."}
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+
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+ >>> data["validation"][2]
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+ {'annot_score': 3.0, 'gem_id': 'gem-opusparcus-validation-1586', 'lang': 'en', 'sent1': 'No promises , okay ?', 'sent2': "I 'm not promising anything ."}
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+
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+ >>> data["train"][1000]
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+ {'annot_score': 0.0, 'gem_id': 'gem-opusparcus-train-12501001', 'lang': 'en', 'sent1': 'Am I beautiful ?', 'sent2': 'Am I pretty ?'}
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  ```
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  ### Data Fields