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title: SummaryProject | |
sdk: docker | |
app_file: src/api.py | |
pinned: false | |
# Project Deep Learning - Text Summarisation tool and it's application programming interface | |
As part of the master course "Neural Network",for this university project, our task is about creating a application, a interface or a python library in the use of NLP(Natural Language Processing) with the help of an artificial neural network system. | |
## Description | |
**Objectives of our project :** | |
Create a interface which allows users to sammrize a long text like press article into a brief version. | |
To achieve this general objective, for the algorithm part, we would like to test two different deep learning methods: setting up a LSTM model and fine tuning Transformer model. | |
For the interface, having a interface building with fastAPI framework and putting the application on Huggingface. | |
## Getting Started | |
### Préparation | |
* Open the link below directing towards our interface on huggingface. | |
``` | |
https://huggingface.co/spaces/EveSa/SummaryProject | |
``` | |
### The interface | |
* 1- Choosing a model for your summarization task (LSTM/Fine-tuned T5) by clicking on the scroll-down list. And click the Select model botton. | |
* 2- Enter your text to summarize in the left section. | |
* 3- Click on 'Go!' botton and you will get your sammary! | |
* 4- Dont forget to reset the App for your next try. The botton is at the right next to 'Go!'. | |
## In case you want to try to execute our scripts : | |
### Préparation | |
* In order to run the script, you need: | |
* 1- Create a virtual environment named .venv | |
``` | |
python3 -m virtualenv .venv | |
source .venv/bin/activate | |
``` | |
* 2- Also install the dependencies | |
``` | |
pip install -U -r requirements.txt | |
``` | |
* You are now ready to execute the scripts ^^ | |
### The programme api.py | |
* Run the script with the command below: | |
``` | |
python3 api.py | |
``` | |
* This code generate the same page as on Huggingface in your browser. To do the task your may follow the steps in the previous section. | |
## Authors | |
Eve Sauvage | |
Estelle SALMON | |
Lingyun GAO | |
## License | |
This project is licensed under the [M2 TAL] License | |