metadata

title: Covid Sentiment Anlaysis With Streamlit
emoji: 🏢
colorFrom: gray
colorTo: pink
sdk: streamlit
sdk_version: 1.28.2
app_file: app.py
pinned: false
license: mit

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

Sentiment Analysis for Covid Feelings using Transformers and Streamlit

This Python script performs sentiment analysis using pre-trained transformer models from the transformers library and integrates it into a Streamlit app to analyze sentiments related to Covid feelings.

Installation

Requirements

Python 3.x
Required libraries: transformers, datasets, streamlit

Install necessary libraries by running:

pip install -q transformers datasets streamlit

Usage

Clone or download the script.
Ensure Python and required libraries are installed.
Run the script in a Python environment.

The script showcases sentiment analysis using a pre-trained model (avichr/heBERT_sentiment_analysis) to classify the sentiment of input text into Negative, Neutral, or Positive categories related to Covid feelings.

Steps:

Preprocesses the input text by handling placeholders for usernames and links.
Utilizes a pre-trained model (bert-base-cased) and the specified sentiment analysis model (avichr/heBERT_sentiment_analysis).
Calculates sentiment scores using softmax probabilities for each sentiment category.
Displays sentiment scores in a Streamlit app based on user input.

Additional Information

The script offers sentiment analysis functionality for Covid-related text input via a Streamlit interface.
Ensure access to the specified model (avichr/heBERT_sentiment_analysis) before running the script.
Users can interact with the Streamlit app by entering text related to Covid feelings to receive sentiment scores for Negative, Neutral, and Positive categories.