Automating Passive-Aggressive Emails with NLP

Have you ever found yourself struggling to craft a perfectly passive-aggressive email? Look no further! This GitHub repository contains a powerful tool that uses cutting-edge Natural Language Processing (NLP) techniques to detect email tones and rewrite them using advanced language models. Let's dive into the details of this fascinating project.

The Tool

This tool, built in Jupyter Notebook, leverages BERT for tone detection and GPT-2 fine-tuned with LoRA for rewriting the emails. The dataset used for training the models is stored in the file tone_dataset.csv. The tool performs two main tasks: tone detection to identify the passive-aggressive nature of the email and rewriting to generate a more polished and professional version of the same message.

# Import necessary libraries
import pandas as pd
import transformers
import torch
import numpy as np

Example

Let's take a look at a snippet of code demonstrating how the tool can be utilized:

# Load the dataset
data = pd.read_csv("tone_dataset.csv")

# Detect tone using BERT
tone = detect_tone(data)

# Rewrite email using GPT-2 fine-tuned with LoRA
rewritten_email = rewrite_email(data, tone)

Conclusion

In conclusion, this tool offers an automated solution for rewriting passive-aggressive emails with the help of state-of-the-art NLP models. With just a few lines of code, you can enhance your communication style and ensure that your messages are received positively. Give it a try and see the magic unfold!

If you're interested in exploring this project further, check out the GitHub repository here. Don't forget to give it a star if you find it useful!