🧠 TibbScholar

TibbScholar is a specialized, 3-billion-parameter language model fine-tuned for medical question-answering. It is based on Meta's Llama-3.2-3B model and is designed to serve as an informational tool for educational and research purposes.

This model was trained on a large subset of the MIRIAD-4.4M dataset to provide concise, structured answers to medical queries.

📌 Model Details

Base Model: unsloth/Llama-3.2-3B-unsloth-bnb-4bit
Fine-tuning Dataset: A 100,000 record subset of MIRIAD-4.4M.
Prompt Format: A simple Question/Answer structure (see below).
Training Framework: Fine-tuned using Unsloth AI's library with QLoRA for efficient training.

📋 Prompt Format

For the model to perform as expected, prompts must follow the structure it was trained on. The prompt should end with Answer: followed by a newline.

Question:
What are the risks in dental implant surgery?

Answer:

💡 How to Use

The model can be easily loaded using the transformers library.

from transformers import pipeline
import torch

pipe = pipeline(
    "text-generation",
    model="Aasher/TibbScholar",
    torch_dtype=torch.bfloat16, # Or float16 for older GPUs
    device_map="auto",
)

prompt = """Question:
What are the risks in dental implant surgery?

Answer:
"""

response = pipe(
    prompt,
    max_new_tokens=256,
    do_sample=True,
    temperature=0.5,
    top_p=0.9,
)

print(response[0]["generated_text"])

⚠️ Intended Use and Limitations

This model is intended solely for academic and informational purposes. It can be a helpful tool for students and researchers exploring medical topics. This model is NOT a medical professional.

The knowledge is limited to its training data and may not be up-to-date.
It can generate incorrect or incomplete information (hallucinate).
Do not use its outputs for clinical decision-making, diagnosis, or treatment.

🚨 Disclaimer: Not for Medical Advice

The information provided by TibbScholar is not a substitute for professional medical advice. Always consult a qualified healthcare provider with any medical questions. The creator of this model assumes no liability for any actions taken based on its output.

🤝 Acknowledgements

Base Model: Meta AI for the Llama 3.2 model.
Dataset: The creators of the MIRIAD dataset.
Training: The Unsloth AI team for their excellent fine-tuning library.

Aasher
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TibbScholar