1.9 KiB
Automatic Term Extraction API
1. Description
In this repo, we wrote an API to inference SloBERTa term extractor, whose model has been trained with RSDO5 corpus. Feel free to check out this repo for better understanding about the methodology.
2. Requirements
Please install all the necessary libraries noted in requirements.txt using this command:
pip install -r requirements.txt
3. Implementation
Download the model from pytorch_model.bin and save it into ./model/term_extractor/.
Run the following command on the terminal:
main.py
A link will be show on the terminal so that you can access to the API and test requests.
* Serving Flask app 'main'
* Debug mode: on
WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead.
* Running on http://127.0.0.1:5000
Press CTRL+C to quit
* Restarting with stat
* Debugger is active!
* Debugger PIN: 185-520-689
We suggest you use POSTMAN or Hoppscotch to test the API with an uploaded file as the output whose format is CONLL-like (plese check out temp_1.conllu). See the demonstration as the image below.
4. Docker version
Run the following command:
docker build -t ate .
docker run -d -p 5000:5000 ate
5. References
The term extraction tool is an updated version of Tran et al. (2022), using the SloBERTa model.
Hanh Thi Hong Tran, Matej Martinc, Andraz Repar, Antoine Doucet and Senja Pollak: A Transformer-based Sequence-labeling Approach to the Slovenian Cross-domain Automatic Term Extraction. Proc. of Jezikovne tehnologije in digitalna humanistika, 2022.
6. Contributors:
- 🐮 TRAN Thi Hong Hanh 🐮
- Matej Martinc
- Senja Pollak