SujitShelar/llama3-medchat-8b-lora

Model Card for Model ID

A 4-bit quantized, LoRA-adapted version of Meta's LLaMA 3 8B model, fine-tuned on the medalpaca/medical_meadow_medical_flashcards dataset for medical question-answering tasks. This model is optimized for efficient inference and training on hardware like NVIDIA A100 GPUs using BF16 precision.

Model Details

• Base model: unsloth/llama-3-8b-bnb-4bit

• Fine-tuned by: Sujit Shelar

• Model type: Auto-regressive transformer (decoder-only)

• Quantization: 4-bit NF4 via bitsandbytes

• PEFT: LoRA (r=4, alpha=8, dropout=0.01)

• Language: English

• License: LLaMA 3 Community License

Model Description

This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.

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Model Sources [optional]

• Repository: SujitShelar/llama3-medchat-8b-lora
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Uses

Direct Use

This model is intended for generating concise, accurate answers to medical questions, making it suitable for applications like:

Medical education tools

Clinical decision support systems

Healthcare chatbots

Medical flashcard applications

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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.

How to Get Started with the Model

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Training Details

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Summary

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Environmental Impact

Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

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