https://github.com/notshrirang/spam-filter-using-albert
This project aims to build a spam filter using a fine-tuned ALBERT (A Lite BERT) Transformer model. The ALBERT model, pre-trained on a large corpus of text, is fine-tuned on a spam detection dataset to create an efficient and accurate spam filter.
https://github.com/notshrirang/spam-filter-using-albert
albert deep-learning huggingface nlp text-classification transformers
Last synced: 3 months ago
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This project aims to build a spam filter using a fine-tuned ALBERT (A Lite BERT) Transformer model. The ALBERT model, pre-trained on a large corpus of text, is fine-tuned on a spam detection dataset to create an efficient and accurate spam filter.
- Host: GitHub
- URL: https://github.com/notshrirang/spam-filter-using-albert
- Owner: NotShrirang
- License: mit
- Created: 2023-10-18T07:29:11.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2024-05-07T04:07:20.000Z (over 1 year ago)
- Last Synced: 2025-04-05T15:29:32.147Z (6 months ago)
- Topics: albert, deep-learning, huggingface, nlp, text-classification, transformers
- Language: Jupyter Notebook
- Homepage: https://spam-filter-using-albert.streamlit.app/
- Size: 205 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Spam Filter using ALBERT
This project aims to build a spam filter using a fine-tuned ALBERT (A Lite BERT) Transformer model. The ALBERT model, pre-trained on a large corpus of text, is fine-tuned on a spam detection dataset to create an efficient and accurate spam filter.
## Table of Contents
- [Overview](#overview)
- [Usage](#usage)
- [Using the Classifier in Your Code](#to-use-this-classifier-in-your-code)
- [Installation](#installation)
- [Running the Streamlit Web App](#run-streamlit-web-app)
- [License](https://github.com/NotShrirang/Spam-Filter-using-ALBERT/blob/main/LICENSE)
## Overview
A transformers based deep learning for binary text classification. There are 2 classes "Spam" and "Not spam".
Model and dataset is deployed on HuggingFace.
- Model: https://huggingface.co/NotShrirang/albert-spam-filter
- Dataset: https://huggingface.co/datasets/NotShrirang/email-spam-filter
## Usage
### To use this classifier in your code:
```py
from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline
tokenizer = AutoTokenizer.from_pretrained("NotShrirang/albert-spam-filter")
model = AutoModelForSequenceClassification.from_pretrained("NotShrirang/albert-spam-filter")
classifier = pipeline('text-classification',
model=model,
tokenizer=tokenizer
)
prediction = classifier("")[0]
```
## Installation:
To run this project, you will need Python and Streamlit installed on your system. You can install the required packages using the provided `requirements.txt` file.
1. Clone Repo:
```sh
git clone https://github.com/NotShrirang/Spam-Filter-using-ALBERT.git
```
2. Change project directory:
```sh
cd Spam-Filter-using-ALBERT
```
3. Get requirements:
```sh
pip install -r requirements.txt
```
## Run Streamlit Web App:
```sh
streamlit run app.py
```