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josephimperial/qwen2.5-7b-prt-hipaa-unstructured-full-policy

sourceHugging Faceupdated 4mo agoView on Hugging Face

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qwen2.5-7b-prt-hipaa-unstructured-full-policy

Qwen2.5-7B-Instruct fine-tuned on Policy Reasoning Traces (PRTs) for binary compliance assessment, as part of an EMNLP 2026 study.

—Train domain: hipaa — unstructured opus-authored PRTs (format isolated).
—Cross-domain holdout: evaluate on the OTHER domain's held-out test set.
—Prompt format: no-policy zero-shot chain-of-thought; the model reasons step-by-step and ends with Final Verdict: COMPLIANT or Final Verdict: NONCOMPLIANT.

Usage

python

from transformers import AutoModelForCausalLM, AutoTokenizer
tok = AutoTokenizer.from_pretrained("josephimperial/qwen2.5-7b-prt-hipaa-unstructured-full-policy")
model = AutoModelForCausalLM.from_pretrained("josephimperial/qwen2.5-7b-prt-hipaa-unstructured-full-policy", torch_dtype="bfloat16", device_map="auto")
msgs = [{"role": "user", "content": PROMPT}]  # see prepare_data.build_prompt