https://github.com/osainz59/aqgsas
Automatic Question Generation and Short Answer Scoring system
https://github.com/osainz59/aqgsas
deep-learning exercise-generator machine-learning question-answering question-generation reading-comprehension text-similarity
Last synced: 10 months ago
JSON representation
Automatic Question Generation and Short Answer Scoring system
- Host: GitHub
- URL: https://github.com/osainz59/aqgsas
- Owner: osainz59
- License: apache-2.0
- Created: 2020-03-26T13:14:54.000Z (about 6 years ago)
- Default Branch: master
- Last Pushed: 2020-05-30T17:43:06.000Z (about 6 years ago)
- Last Synced: 2025-04-13T01:24:27.383Z (about 1 year ago)
- Topics: deep-learning, exercise-generator, machine-learning, question-answering, question-generation, reading-comprehension, text-similarity
- Language: Python
- Size: 298 KB
- Stars: 7
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Automatic Question Generation and Short Answer Scoring system
## Instalation
The first think you have to do is install the requirements. You can do it with the following command:
```bash
pip install -r requirements.txt
```
### Question Generation model
The model used on this application is the checkpoint provided by [UniLM](https://github.com/microsoft/unilm) that you can download from here: [here](https://drive.google.com/open?id=1JN2wnkSRotwUnJ_Z-AbWwoPdP53Gcfsn).
Once you downloaded the checkpoint create the `pretrained_models/` directory and save the checkpoint there.
## How to run
The `host` and `port` arguments are only necessary if you want to open a server through internet. If you want to just open the server for local usage skip those parameters.
### Linux
```bash
export FLASK_APP=server.py
flask run --host=YOUR_LOCAL_IP --port=PORT
```
### Windows
```powershell
$env:FLASK_APP = "server.py"
flask run --host=YOUR_LOCAL_IP --port=PORT
```
## Credits
This application is powered by the following resources:
* Transformers (🤗 [Huggingface](https://github.com/huggingface/transformers))
* Flair ([FlairNLP](https://github.com/flairNLP/flair))
* UniLM ([Microsoft](https://github.com/microsoft/unilm))