README.md

metadata

title: Sentiment Analysis on Encrypted Data with FHE
emoji: 🥷💬
colorFrom: yellow
colorTo: yellow
sdk: gradio
sdk_version: 3.2
app_file: app.py
pinned: true
tags:
  - FHE
  - PPML
  - privacy
  - privacy preserving machine learning
  - homomorphic encryption
  - security
python_version: 3.9

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

Sentiment Analysis With FHE

Running the application on your machine

In this directory, ie sentiment-analysis-with-transformer, you can do the following steps.

Do once

• First, create a virtual env and activate it:

python3.9 -m venv .venv
source .venv/bin/activate

• Then, install required packages:

pip3 install -U pip wheel setuptools --ignore-installed
pip3 install -r requirements.txt --ignore-installed

• If not on Linux, or if you want to compile the FHE algorithms by yourself:

python3 compile.py

Check it finish well (with a "Done!").

Do each time you relaunch the application

• Then, in a terminal Tab 1:

source .venv/bin/activate
uvicorn server:app

Tab 1 will be for the Server side.

• And, in another terminal Tab 2:

source .venv/bin/activate
python3 app.py

Tab 2 will be for the Client side.

Interacting with the application

Open the given URL link (search for a line like Running on local URL: http://127.0.0.1:8888/ in your Terminal 2).

Training a new model

The notebook SentimentClassification.ipynb provides a way to train a new model.

Before running the notebook, you need to download the data.

bash download_data.sh