README.md

metadata

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:

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:

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