OhioCustodyBERT

A domain-specific legal AI system for Ohio family law, child custody, and parental alienation. Built from the ground up with over 13,000 curated training examples from Ohio statutes, appellate decisions, Supreme Court cases, and legal reference materials.

⚠️ This is a legal research tool, not legal advice. Always consult a licensed attorney for legal matters.

---

Two Ways to Use This

🟢 Simple: One File, One Command

Download a single GGUF file and run it. No setup, no configuration, no Python required.

# Download the GGUF from the Qwen adapter repo, then:
ollama create ohio-custody -f Modelfile
ollama run ohio-custody
>>> What are the best interest factors for custody under Ohio law?

What you get: A Qwen3.5-9B model fine-tuned on 13,346 Ohio family law Q&A pairs. It knows Ohio statutes, case law, and court procedures. Ask it anything about Ohio custody law and it responds with citations.

👉 Download the GGUF

---

🔵 Advanced: The Full Legal Agent Council

Deploy a multi-agent system where specialized AI models cross-examine each other — like having a legal team debate your case. Multiple models, each with a different perspective, produce consensus-based legal analysis.

What you get: 6 agents analyzing your question from different angles (statute law, case law, procedure, adversary's argument), a synthesis judge that resolves conflicts, and a verifier that fact-checks every citation. When the models agree, you can be confident. When they disagree, you've found where the law is genuinely unclear.

👉 Keep reading below for the full architecture.

---

Why This Exists

The Ohio family court system processes thousands of custody cases annually. Parents — especially pro se litigants — face a legal system built on decades of case law, statutes, and procedural rules that are nearly impossible to navigate without expensive legal counsel.

OhioCustodyBERT aims to democratize access to Ohio family law knowledge by providing AI models trained specifically on:

• Ohio Revised Code (ORC) Chapter 3109 and related family law statutes
• Ohio Rules of Evidence (Evid.R. 101-1103) — authentication, hearsay, cross-examination, expert testimony
• Ohio Administrative Code (OAC) custody and child welfare rules
• Appellate court decisions on custody, parental alienation, and visitation
• US Supreme Court precedent on parental rights (Santosky, Stanley, Troxel)
• Ohio Supreme Court reports, bench cards, and practice guides
• Trial advocacy techniques — cross-examination methods, evidence foundation, objection handling

---

The Legal Agent Council

OhioCustodyBERT is not a single model — it's a multi-agent legal reasoning system where specialized AI models work together to provide comprehensive legal analysis. Each model is fine-tuned on the same curated Ohio family law corpus, but serves a different role.

Architecture

User Query
    │
    ▼
┌─────────────────────────────┐
│  ① BERT Retriever           │ ← OhioCustodyBERT (this model)
│  Finds relevant statutes,   │    ModernBERT-base, 149.7M params
│  case law, and rules        │
└──────────┬──────────────────┘
           │ Retrieved context
           ▼
┌─────────────────────────────┐
│  ② Statute Agent            │ ← OhioCustodyBERT-Qwen3.5-9B (LoRA)
│  "What does the law say?"   │    Analyzes applicable statutes
├─────────────────────────────┤
│  ③ Case Law Agent           │ ← Same base, different prompt
│  "What have courts held?"   │    Finds binding precedent
├─────────────────────────────┤
│  ④ Procedure Agent          │ ← Qwen3-30B-A3B (MoE, planned)
│  "Was due process followed?"│    Procedural compliance check
├─────────────────────────────┤
│  ⑤ Adversary Agent          │ ← OhioCustodyBERT-Qwen3.5-9B (LoRA)
│  "What's the other side?"   │    Steel-mans the opposition
└──────────┬──────────────────┘
           │ All analyses
           ▼
┌─────────────────────────────┐
│  ⑥ Synthesis Judge          │ ← QwQ-32B (deep reasoning)
│  Weighs all perspectives,   │    Produces final analysis with
│  resolves conflicts         │    confidence scoring
└──────────┬──────────────────┘
           │ Final analysis
           ▼
┌─────────────────────────────┐
│  ⑦ BERT Verifier            │ ← OhioCustodyBERT (this model)
│  Fact-checks citations,     │    Catches hallucinated case law
│  validates statute refs     │    and incorrect statute numbers
└─────────────────────────────┘

Why Multiple Models?

Same data, different architectures = meaningful consensus. When all models agree on a legal analysis, confidence is high. When they disagree, the disagreement reveals where the law is ambiguous or the facts need closer examination — which is exactly what a good lawyer would identify.

---

Models in This System

Model	HuggingFace	Role	Architecture
OhioCustodyBERT	This repo	Retriever + Verifier	ModernBERT-base (149.7M)
OhioCustodyBERT-Qwen3.5-9B	Adapter repo	Generative Agents	Qwen3.5-9B + LoRA
Training Corpus	Dataset	All training data	13,346 SFT pairs + raw corpus

---

This Model: ModernBERT Retriever + Verifier

What It Does

• Semantic retrieval: Find the most relevant statutes, rules, and case law for a given legal question
• Classification: Identify legal issues (custody type, parental alienation indicators, due process violations)
• NER: Extract legal entities (judge names, case citations, statute references)
• Citation verification: Validate that LLM-generated citations point to real cases and statutes

Model Details

Base	ModernBERT-base (149.7M params)
Domain	Ohio family law, child custody, parental alienation
Training	Masked Language Modeling on curated Ohio legal corpus
Version	v0.1 (v0.2 training in progress — full corpus)
License	Apache 2.0

---

Training Corpus (v24 — March 2026)

All models in the Legal Agent Council are trained on the same curated corpus:

SFT Training Data — 13,346 unique pairs

Source	Pairs	Description
Ohio Revised Code	4,145	R.C. 3109, 2919, 2151, 3111, 3127, 3105 — statutes on custody, DV, juvenile, paternity, UCCJEA, divorce
Ohio Administrative Code	3,849	OAC rules on child welfare, custody evaluation, court procedures
Curated Q&A	2,288	Hand-audited pairs from opinion analysis, case strategy, verified datasets
CourtListener opinions	1,374	Ohio appellate court custody and family law decisions
Reference materials	732	Ohio SC task force reports, bench cards, GAL guides, custody evaluator toolkit
Targeted opinions	560	Ohio appellate, Ohio SC, and SCOTUS parental rights decisions
Sperm donor cases	154	R.C. 3111 paternity and donor rights case law
OhioFamilyRights	113	Family law reform advocacy, legislative testimony, case analyses
Juvenile court	75	Juvenile court procedures and delinquency
Gemini-generated	56	Cloud-generated Q&A from corpus documents

Generators: Gemini 2.5 Flash, qwen3-coder:480b, Ollama local models, manual curation

Raw Corpus

Source	Records	Size
Ohio Revised Code (19 chapters)	1,034 sections	3.0 MB
Ohio Administrative Code (19 divisions)	1,283 rules	7.3 MB
CourtListener opinions (OH App, SC, SCOTUS)	259 opinions	14 MB
Reference materials	941 records	4.0 MB
Parental alienation research	55 papers	—
Ohio Rules of Evidence	89 rules (all 11 articles)	170 KB

Key Cases Covered

• SCOTUS: Santosky v. Kramer, Stanley v. Illinois, Troxel v. Granville, Michael H. v. Gerald D., Lehr v. Robertson
• Ohio SC: In re Murray, In re Bonfield, Shearer v. Shearer, Felton, Davis v. Flickinger
• Topics: Best interest standard (R.C. 3109.04), shared parenting, parental alienation, GAL standards, custody evaluation, DV protective orders, contempt, UCCJEA jurisdiction, evidence authentication, hearsay exceptions, cross-examination

---

Quick Start

Using This Model (ModernBERT — Retrieval/Classification)

from transformers import AutoModel, AutoTokenizer

model = AutoModel.from_pretrained("Roderick3rd/OhioCustodyBERT")
tokenizer = AutoTokenizer.from_pretrained("Roderick3rd/OhioCustodyBERT")

# Encode legal text for semantic search
text = "What factors does R.C. 3109.04 consider for shared parenting?"
inputs = tokenizer(text, return_tensors="pt", truncation=True, max_length=512)
outputs = model(**inputs)
embeddings = outputs.last_hidden_state.mean(dim=1)

Using the Generative Model (Qwen3.5-9B — Legal Analysis)

from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel

base = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3.5-9B")
model = PeftModel.from_pretrained(base, "Roderick3rd/OhioCustodyBERT-Qwen3.5-9B")
tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen3.5-9B")

Using via Ollama (Easiest)

ollama run ohio-custody
>>> What are the best interest factors under R.C. 3109.04?

---

Limitations

• Ohio-specific: Trained primarily on Ohio law — may not generalize to other states
• Not legal advice: This is a research tool, not a substitute for a licensed attorney
• v0.1: Current model trained on limited examples; v0.2 will substantially improve quality
• Case law currency: Training data has a cutoff; recent decisions may not be reflected
• Classification bias: Reflects the Ohio statutory framework (R.C. 3109.04 best interest factors)

---

Intended Use

Use Case	✅ Appropriate	❌ Not Appropriate
Legal research	Identifying relevant statutes and cases	Generating court filings
Case preparation	Understanding legal standards and precedent	Making custody recommendations
Trial preparation	Practicing cross-examination and evidence presentation	Replacing legal counsel
Education	Learning Ohio family law framework	Autonomous legal decision-making
Citation checking	Verifying case law references	—
Evidence rules	Understanding authentication and hearsay	**— **

---

Project Status

Component	Status	Notes
ModernBERT v0.1	✅ Live	149.7M params, 864 examples
ModernBERT v0.2	🔄 Training	Full corpus MLM retraining
Qwen3.5-9B LoRA	🔄 Training	13,346 pairs, MLX on M4 Pro 48GB
v24 Corpus	✅ Complete	13,346 pairs from 19 sources
Legal Agent Council	🔄 In Development	6-agent pipeline, sequential model swap
Kaggle Datasets	✅ Published	ohio-legal-corpus, pa-references, ohio-custody-sft-v21

---

Citation

@misc{ohiocustodybert2026,
  title={OhioCustodyBERT: Domain-Specific Legal AI System for Ohio Family Law},
  author={Roderick Mullins},
  year={2026},
  howpublished={HuggingFace: Roderick3rd/OhioCustodyBERT}
}

Related Resources

• Generative Model: OhioCustodyBERT-Qwen3.5-9B — LoRA adapter for legal analysis generation
• Training Corpus: OhioCustodyBERT-corpus — Full dataset with SFT pairs
• Kaggle: ohio-legal-corpus, pa-references