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@ -65,7 +65,6 @@ Sahrawat, Dhruva, Debanjan Mahata, Haimin Zhang, Mayank Kulkarni, Agniv Sharma,
### 🛑 Limitations
* This keyphrase extraction model is very domain-specific and will perform very well on abstracts of scientific papers. It's not recommended to use this model for other domains, but you are free to test it out.
* Only works for English documents.
* For a custom model, please consult the [training notebook]() for more information.
### ❓ How To Use
```python
@ -139,8 +138,6 @@ print(keyphrases)
You can find more information in the [paper](https://dl.acm.org/doi/10.3115/1119355.1119383).
## 👷‍♂️ Training Procedure
For more in detail information, you can take a look at the [training notebook]().
### Training Parameters
| Parameter | Value |
@ -256,7 +253,5 @@ The model achieves the following results on the Inspec test set:
|:-----------------:|:----:|:----:|:----:|:----:|:----:|:-----:|:----:|:----:|:----:|
| Inspec Test Set | 0.45 | 0.40 | 0.39 | 0.33 | 0.53 | 0.38 | 0.47 | 0.57 | 0.49 |
For more information on the evaluation process, you can take a look at the keyphrase extraction [evaluation notebook]().
## 🚨 Issues
Please feel free to start discussions in the Community Tab.