Modelpublic

nihanthnaidu007/llama-3.1-8b-pharma-compliance-qlora-v3

sourceHugging Facellama3.1updated 7mo agoView on Hugging Face

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Model Card

LLaMA-3.1-8B Pharmaceutical Compliance QLoRA

Fine-tuned LLaMA-3.1-8B-Instruct on 500 FDA pharmaceutical compliance instruction pairs using QLoRA + Unsloth.

Model Details

Property	Value
Base Model	meta-llama/Meta-Llama-3.1-8B-Instruct
Method	QLoRA 4-bit NF4 + LoRA rank 64
Framework	Unsloth (2x faster, 60% less VRAM)
Domain	FDA CFR Title 21, GMP, ICH guidelines
Training Samples	450
Epochs	3
GPU	A100 40GB

Domain Coverage

—21 CFR Part 210/211 (cGMP)
—21 CFR Part 201 (Drug labeling)
—ICH Q8/Q9/Q10 (Pharmaceutical quality)
—OOS investigations, CAPA writing
—Deviation reports, process validation
—Bioequivalence requirements

Usage

python

from unsloth import FastLanguageModel

model, tokenizer = FastLanguageModel.from_pretrained(
    model_name="nihanthnaidu007/llama-3.1-8b-pharma-compliance-qlora-v3",
    max_seq_length=1024,
    load_in_4bit=True,
)
FastLanguageModel.for_inference(model)

Author

Nihanth Naidu Kalisetti — AI Engineer W&B Run: https://wandb.ai/nihanthnaidu-kalisetti-long-island-university/llama-pharma-qlora/runs/ai5sxvun