Update README.md

README.md

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 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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+---
+
+# 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:
+
+```bash
+pip install -q transformers datasets streamlit
+```
+
+## Usage
+
+1. Clone or download the script.
+2. Ensure Python and required libraries are installed.
+3. 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:
+1. Preprocesses the input text by handling placeholders for usernames and links.
+2. Utilizes a pre-trained model (`bert-base-cased`) and the specified sentiment analysis model (`avichr/heBERT_sentiment_analysis`).
+3. Calculates sentiment scores using softmax probabilities for each sentiment category.
+4. 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.
+
+