README.md

metadata

title: Text Sentiment Classifier
emoji: 🧠
sdk: gradio
app_file: app.py

Text-Sentiment-Classifier-API

This project is a simple REST API for sentiment analysis built with FastAPI and HuggingFace Transformers. It uses the distilbert-base-uncased-finetuned-sst-2-english model to classify English text as positive, negative or (rarely) neutral, and it returns a confidence score.

🚀 Features

• RESTful API with FastAPI

• Pre-trained BERT-based sentiment model

• JSON input and output

• Interactive Swagger UI at /docs

📦 Model

The API uses:

distilbert-base-uncased-finetuned-sst-2-english

A lightweight version of BERT fine-tuned on the SST-2 dataset for sentiment classification.

Example

Request: POST /predict { "text": "I absolutely love this product!" }

Response: { "sentiment": "positive", "confidence": 0.9981 }

📁 File Structure

.
├── main.py # API implementation
├── requirements.txt # Python dependencies
└── README.md # Project documentation

🚀 How to Use

1. Enter any English sentence in the input box
2. Click Submit
3. View the sentiment label and confidence

🚀 How to Deploy on Hugging Face Spaces

1. Create a Hugging Face account
   Sign up at https://huggingface.co/join

2. Create a new Space Go to https://huggingface.co/spaces and click Create new Space

3. Fill out the form

   • Space name: text-sentiment-api (or your choice)
   • SDK: Gradio
   • Visibility: Public or Private

4. Upload the files

   • app.py
   • requirements.txt
   • README.md (this file)

5. Wait for the build Hugging Face will automatically install dependencies and launch the app

6. Access your app