intentfx/TaylorSwiftFineTunedChatBot

TaylorSwiftChatbot 🎸✨

A LoRA fine-tuned version of Qwen2.5-0.5B-Instruct, trained on a curated dataset of conversational examples inspired by Taylor Swift's interviews, public appearances, and speaking style.

⚠️ This is an experimental fan project intended for research and educational purposes only. It is not affiliated with or endorsed by Taylor Swift.

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Model Details

• Base Model: Qwen/Qwen2.5-0.5B-Instruct
• Fine-Tuning Method: LoRA (PEFT)
• Training Hardware: NVIDIA RTX 3050 Laptop GPU (6GB VRAM)
• Training Time: ~15 minutes
• Dataset Size: ~367 conversational examples
• Epochs: 5

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Goal

The goal of this project is to explore whether a small language model can learn:

• Conversational tone
• Storytelling style
• Emotional responses
• Interview mannerisms
• Personality traits and speaking patterns

This model focuses on style imitation, not factual knowledge.

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Current Status

Version 1 is an early prototype.

Strengths

✅ Captures some aspects of Taylor's reflective and conversational tone.

✅ Produces longer and more personal responses than the base model.

✅ Demonstrates personality conditioning despite the small dataset.

Limitations

❌ Limited dataset size.

❌ Can still sound like the base Qwen model.

❌ May hallucinate facts or generate inaccurate information.

❌ Personality consistency is not yet reliable.

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Usage

Load the Base Model

from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel
import torch

BASE_MODEL = "Qwen/Qwen2.5-0.5B-Instruct"
ADAPTER = "intentfx/TaylorSwiftChatbot"

tokenizer = AutoTokenizer.from_pretrained(BASE_MODEL)

base_model = AutoModelForCausalLM.from_pretrained(
    BASE_MODEL,
    torch_dtype=torch.float16,
    device_map="auto"
)

model = PeftModel.from_pretrained(
    base_model,
    ADAPTER
)

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Example Prompt

messages = [
    {
        "role": "system",
        "content": (
            "You are Taylor Swift, the singer-songwriter. "
            "Speak warmly, thoughtfully, and introspectively."
        )
    },
    {
        "role": "user",
        "content": "How do you approach songwriting?"
    }
]

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Future Improvements

• Larger and higher quality dataset
• More interview and fan interaction examples
• Better system prompts
• Synthetic conversational data generation
• Fine-tuning on larger base models (1.5B to 3B)
• Improved personality consistency

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Disclaimer

This model attempts to imitate a public speaking style and should not be considered a representation of the real person's beliefs, opinions, or future statements.

This project is intended solely for:

• Research
• Education
• Experimentation with LLM fine-tuning and personality modeling

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Acknowledgements

• Qwen Team for the base model.
• Hugging Face for open-source tooling.
• PEFT and TRL libraries for efficient fine-tuning.

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Built by Intent (Sudeep Mukul) 🚀