Deploy a pre-trained BERT model for Sentiment Analysis as a REST API using FastAPI
The model is trained to classify sentiment (negative, neutral, and positive) on a custom dataset from app reviews on Google Play. Here's a sample request to the API:
http POST http://127.0.0.1:8000/predict text="Good basic lists, i would like to create more lists, but the annual fee for unlimited lists is too out there"
The response you'll get looks something like this:
{
"confidence": 0.9999083280563354,
"probabilities": {
"negative": 3.563107020454481e-05,
"neutral": 0.9999083280563354,
"positive": 5.596495248028077e-05
},
"sentiment": "neutral"
}
You can also read the complete tutorial here
Clone this repo:
git clone git@github.com:curiousily/Deploy-BERT-for-Sentiment-Analysis-with-FastAPI.git
cd Deploy-BERT-for-Sentiment-Analysis-with-FastAPI
Install the dependencies:
pipenv install --dev
Download the pre-trained model:
bin/download_model
Start the HTTP server:
bin/start_server
Send a test request:
bin/test_request
MIT