Sharpener9290/hcup-llm-humanizer

HCUP LLM Humanizer Adapter

Model Overview

• Base Model: mistralai/Mistral-7B-v0.3
• Adapter Type: LoRA (QLoRA 4-bit)
• Purpose: Humanized, non-AI-sounding clinical manuscript generation from HCUP administrative data

Training Data

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

Humanization Rules

• AVOID: Furthermore, It is important to note, In conclusion, Delve into, Notably
• USE: short declarative sentences, clinical connectors (Then, But, So)
• TONE: confident, direct, patient-centered clinical framing

LoRA Config

• rank=16, alpha=32
• target_modules: q_proj, v_proj
• dropout: 0.05

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")
tokenizer = AutoTokenizer.from_pretrained("mistralai/Mistral-7B-v0.3")