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--- |
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title: Sentiment Analysis on Encrypted Data with FHE |
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emoji: 🥷💬 |
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colorFrom: yellow |
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colorTo: yellow |
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sdk: gradio |
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sdk_version: 3.2 |
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app_file: app.py |
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pinned: true |
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tags: |
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- FHE |
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- PPML |
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- privacy |
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- privacy preserving machine learning |
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- homomorphic encryption |
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- security |
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python_version: 3.9 |
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duplicated_from: zama-fhe/encrypted_sentiment_analysis |
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--- |
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference |
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# Sentiment Analysis With FHE |
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## Running the application on your machine |
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In this directory, ie `sentiment-analysis-with-transformer`, you can do the following steps. |
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### Do once |
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- First, create a virtual env and activate it: |
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```bash |
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python3.9 -m venv .venv |
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source .venv/bin/activate |
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``` |
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- Then, install required packages: |
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```bash |
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pip3 install -U pip wheel setuptools --ignore-installed |
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pip3 install -r requirements.txt --ignore-installed |
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``` |
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- If not on Linux, or if you want to compile the FHE algorithms by yourself: |
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```bash |
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python3 compile.py |
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``` |
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Check it finish well (with a "Done!"). |
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### Do each time you relaunch the application |
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- Then, in a terminal Tab 1: |
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```bash |
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source .venv/bin/activate |
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uvicorn server:app |
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``` |
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Tab 1 will be for the Server side. |
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- And, in another terminal Tab 2: |
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```bash |
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source .venv/bin/activate |
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python3 app.py |
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``` |
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Tab 2 will be for the Client side. |
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## Interacting with the application |
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Open the given URL link (search for a line like `Running on local URL: http://127.0.0.1:8888/` in your Terminal 2). |
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## Training a new model |
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The notebook SentimentClassification.ipynb provides a way to train a new model. |
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Before running the notebook, you need to download the data. |
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```bash |
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bash download_data.sh |
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``` |
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