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  1. README.md +1 -2
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@@ -28,7 +28,7 @@ This metric implements the evaluation harness for datasets translated with the B
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  4. Run the metric on the `predictions`, `languages`, and `question_infos`.
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  5. The result of the metric is a tuple where the first is a metric dict and the second value is the results for each prediction.
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- ```python
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  import evaluate
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  from datasets import load_dataset
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  import os
@@ -46,7 +46,6 @@ for row in ds:
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  # Replace this with however you generate and postprocess predictions.
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  predictions.append(model.generate(row['signature_with_docstring']))
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-
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  metric = evaluate.load("bc_eval")
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  metrics, results = metric.compute(
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  predictions=predictions, languages=languages, question_dicts=question_infos, k=[1]
 
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  4. Run the metric on the `predictions`, `languages`, and `question_infos`.
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  5. The result of the metric is a tuple where the first is a metric dict and the second value is the results for each prediction.
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+ ```Python
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  import evaluate
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  from datasets import load_dataset
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  import os
 
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  # Replace this with however you generate and postprocess predictions.
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  predictions.append(model.generate(row['signature_with_docstring']))
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  metric = evaluate.load("bc_eval")
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  metrics, results = metric.compute(
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  predictions=predictions, languages=languages, question_dicts=question_infos, k=[1]