Cover Letter AI Assistant (Deep Learning Project)

An end-to-end NLP application that helps users write, complete, and analyze cover letters using Transformer-based models. The system combines BERT fine-tuned classifiers with a Qwen causal language model and exposes the functionality through an interactive CLI.

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Features

• Intent Detection: Fine-tuned BERT model classifies user intent (write, complete, analyze, exit)
• Cover Letter Generation: Qwen2.5 causal language model generates personalized cover letters
• Sentence Auto-Completion: Continues partial cover letter drafts in a professional tone
• Cover Letter Analysis: BERT-based sentence classification (name, skills, education, objective, other)
• GPU Support: CUDA-enabled training and inference when available

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Tech Stack

• PyTorch
• Hugging Face Transformers & Datasets
• BERT (Sequence Classification)
• Qwen2.5 (Causal Language Modeling)
• Pandas
• scikit-learn
• CUDA / GPU Acceleration

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How to Run

1. Open cover_letter_generator.ipynb in Google Colab or Jupyter
2. Run cells top-to-bottom to install dependencies and train/load models
3. Start the interactive assistant:

   interactive_cli()