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@ -67,7 +67,7 @@ Sahrawat, Dhruva, Debanjan Mahata, Haimin Zhang, Mayank Kulkarni, Agniv Sharma,
* Only works for English documents.
* For a custom model, please consult the [training notebook]() for more information.
### ❓ How to use
### ❓ How To Use
```python
from transformers import (
TokenClassificationPipeline,
@ -247,7 +247,7 @@ def extract_keyphrases(example, predictions, tokenizer, index=0):
```
## 📝 Evaluation results
## 📝 Evaluation Results
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.
The model achieves the following results on the Inspec test set: