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https://github.com/alrafi004/text-sentiment-analysis-using-caikit-and-hugging-face
This project is a Text Sentiment Analysis application that leverages the power of Caikit and Hugging Face to perform sentiment analysis on textual data. The goal of this project is to provide an accessible and efficient way for users to analyze the sentiment of text inputs, such as reviews, comments, or any arbitrary text samples.
https://github.com/alrafi004/text-sentiment-analysis-using-caikit-and-hugging-face
caikit huggingface python sentiment-analysis
Last synced: 10 days ago
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This project is a Text Sentiment Analysis application that leverages the power of Caikit and Hugging Face to perform sentiment analysis on textual data. The goal of this project is to provide an accessible and efficient way for users to analyze the sentiment of text inputs, such as reviews, comments, or any arbitrary text samples.
- Host: GitHub
- URL: https://github.com/alrafi004/text-sentiment-analysis-using-caikit-and-hugging-face
- Owner: AlRafi004
- Created: 2024-11-05T15:26:35.000Z (3 months ago)
- Default Branch: main
- Last Pushed: 2024-11-09T04:15:18.000Z (3 months ago)
- Last Synced: 2024-12-10T14:12:34.244Z (2 months ago)
- Topics: caikit, huggingface, python, sentiment-analysis
- Language: Python
- Homepage:
- Size: 62.5 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Text Sentiment Analysis using Caikit and Hugging Face
This project implements text sentiment analysis using Caikit and Hugging Face. This allows users to perform sentiment analysis on text samples and provides insight into the emotional tone of the content (positive or negative).
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## Table of Contents
- [Features](#features)
- [Installation](#installation)
- [Usage](#usage)
- [Project Structure](#project-structure)
- [Requirements](#requirements)
- [Explanation Continued](#explanation-continued)
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## Features
- Sentiment analysis of text inputs.
- Built with the Caikit runtime to manage AI models.
- Utilizes Hugging Face models for advanced natural language processing.
- Easy-to-use client application for querying the model.
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## Installation
To set up the project locally, follow these steps:
1. Clone the repository:
```bash
git clone https://github.com/AlRafi004/Text-Sentiment-Analysis-using-Caikit-and-Hugging-Face.git
cd Text-Sentiment-Analysis-using-Caikit-and-Hugging-Face
2. Install the required dependencies:
```bash
pip install -r requirements.txt
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## Usage
1. Start the Caikit runtime:
```bash
python start_runtime.py
2. In a new terminal, run the client application to perform sentiment analysis:
```bash
python client.py
3. The client will provide text input, and you can see the sentiment analysis results in the terminal.
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## Project Structure
```bash
text-sentiment/ # Top-level package directory
├── start_runtime.py # Wrapper to start the Caikit runtime as a gRPC server
├── client.py # Client to call the Caikit runtime for inference
├── requirements.txt # Specifies library dependencies
├── models/ # Directory containing Caikit model metadata and artifacts
│ └── text_sentiment/config.yml # Metadata defining the Caikit text sentiment model
└── text_sentiment/ # Directory defining Caikit module(s)
├── config.yml # Configuration for the module and model input/output
├── __init__.py # Makes the data_model and runtime_model packages visible
├── data_model/ # Directory for the Caikit data model
│ ├── classification.py # Data class representing AI model attributes
│ └── __init__.py # Makes the data model class visible
└── runtime_model/ # Directory for the Caikit model wrapper
├── hf_module.py # Class to bootstrap the AI model in Caikit
└── __init__.py # Makes the module class visible
```
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## Requirements
* Python 3.7 or higher
* Caikit
* Hugging Face Transformers
* Other dependencies as listed in requirements.txt
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## Explanation Continued
For further explanation is located in the README.md file inside the Analysis Sentiment file.
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