---
title: Covid Sentiment With Gradio
emoji: 📈
colorFrom: purple
colorTo: pink
sdk: gradio
sdk_version: 4.5.0
app_file: app.py
pinned: false
license: mit
---

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


---

# Sentiment Analysis with Transformers and Gradio

This script performs sentiment analysis using pre-trained transformer models from the `transformers` library and sets up a user interface using `Gradio` for interaction.

## Installation

### Requirements
- Python 3.x
- Required libraries: `transformers`, `datasets`, `gradio`

Install necessary libraries by running:

```bash
pip install -q transformers datasets gradio
```

## 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 demonstrates sentiment analysis using a pre-trained model (`avichr/heBERT_sentiment_analysis`) to classify the sentiment of input text into `Negative`, `Neutral`, or `Positive` categories.

### 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. Performs sentiment analysis on the provided text, showcasing the confidence scores for each sentiment category.

## Additional Information

- The script demonstrates two methods for sentiment analysis using both PyTorch-based and TensorFlow-based transformer models.
- The Gradio interface allows users to input text and get a sentiment label prediction based on the pre-trained model.

Please ensure proper environment setup and access to the specified model (`avichr/heBERT_sentiment_analysis`) before running the script 

---

# Sentiment Analysis with Transformers and Gradio

This script performs sentiment analysis using pre-trained transformer models from the `transformers` library and sets up a user interface using `Gradio` for interaction.

## Installation

### Requirements
- Python 3.x
- Required libraries: `transformers`, `datasets`, `gradio`

Install necessary libraries by running:

```bash
pip install -q transformers datasets gradio
```

## 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 demonstrates sentiment analysis using a pre-trained model (`avichr/heBERT_sentiment_analysis`) to classify the sentiment of input text into `Negative`, `Neutral`, or `Positive` categories.

### 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. Performs sentiment analysis on the provided text, showcasing the confidence scores for each sentiment category.

## Additional Information

- The script demonstrates two methods for sentiment analysis using both PyTorch-based and TensorFlow-based transformer models.
- The Gradio interface allows users to input text and get a sentiment label prediction based on the pre-trained model.

Please ensure proper environment setup and access to the specified model (`avichr/heBERT_sentiment_analysis`) before running