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@@ -67,7 +67,7 @@ Sahrawat, Dhruva, Debanjan Mahata, Haimin Zhang, Mayank Kulkarni, Agniv Sharma,
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  * Only works for English documents.
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  * For a custom model, please consult the [training notebook]() for more information.
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- ### ❓ How to use
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  ```python
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  from transformers import (
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  TokenClassificationPipeline,
@@ -247,7 +247,7 @@ def extract_keyphrases(example, predictions, tokenizer, index=0):
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  ```
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- ## πŸ“ Evaluation results
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  Traditional evaluation methods are the precision, recall and F1-score @k,m where k is the number that stands for the first k predicted keyphrases and m for the average amount of predicted keyphrases.
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  The model achieves the following results on the Inspec test set:
 
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  * Only works for English documents.
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  * For a custom model, please consult the [training notebook]() for more information.
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+ ### ❓ How To Use
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  ```python
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  from transformers import (
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  TokenClassificationPipeline,
 
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  ```
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+ ## πŸ“ Evaluation Results
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  Traditional evaluation methods are the precision, recall and F1-score @k,m where k is the number that stands for the first k predicted keyphrases and m for the average amount of predicted keyphrases.
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  The model achieves the following results on the Inspec test set: