Sharpener9290/hcup-llm-humanizer-v1

Model Card for HCUP LLM Humanizer Adapter

Model Details

• —Base Model: mistralai/Mistral-7B-v0.3
• —Adapter Type: LoRA (QLoRA 4-bit)
• —Training: DPO on clinical writing humanization pairs

Purpose

Trained to produce humanized, non-AI-sounding clinical manuscripts using HCUP administrative data patterns.

Usage

from peft import PeftModel, AutoModelForCausalLM, AutoTokenizer
import torch

base = AutoModelForCausalLM.from_pretrained(
    "mistralai/Mistral-7B-v0.3",
    torch_dtype=torch.float16,
    device_map="auto"
)
model = PeftModel.from_pretrained(base, "Sharpener9290/hcup-llm-humanizer-v1")
tokenizer = AutoTokenizer.from_pretrained("mistralai/Mistral-7B-v0.3")

Training Data

• —400 instruction pairs from HCUP corpus (nis, neds, trinetx, hcup_general)
• —50 preference pairs for DPO humanization style transfer

LoRA Config

• —rank=16, alpha=32
• —targetmodules: qproj, v_proj
• —dropout=0.05