jeremy-gemma4

Jeremy AI — Gemma 4 E4B Legal Procedural Guidance

A QLoRA adapter fine-tuned on Gemma 4 E4B for legal procedural guidance. Built for the Gemma 4 Good Hackathon as part of the Pro Se Network — free legal AI infrastructure for self-represented litigants.

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Mission

80% of low-income Americans cannot afford a lawyer. Jeremy AI is a nonprofit infrastructure project that gives self-represented litigants a trained legal procedural guide — free, self-hostable, and deployable anywhere in the world at $0 per conversation.

The choice of Gemma 4 open weights is a mission requirement, not a technical preference. A per-token API bill is not acceptable for legal aid organizations.

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What Jeremy Does

Jeremy is a legal procedural guidance engine — not a legal advice chatbot. It:

• Understands a user's legal situation in plain English
• Extracts structured legal facts (dates, entities, deadlines, risk signals)
• Explains procedures, deadlines, and next steps in plain English
• Helps draft Answers, EEOC Charges, Motions to Dismiss
• Routes high-risk situations (custody, criminal) to attorney referral

It runs on top of a deterministic rule engine covering 12 areas of law across 13 U.S. jurisdictions. The LLM never decides the law — rules are loaded from verified JSON databases.

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Training

Dataset

5,196 legal Q&A pairs from 5 free sources — israelburns/jeremy-training-data

Training Configuration

Trainable Parameters

42,401,792 of 8,038,558,240 total (0.53%)

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Usage

from peft import PeftModel
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch

base_model = "google/gemma-4-E4B-it"
adapter = "israelburns/jeremy-gemma4"

tokenizer = AutoTokenizer.from_pretrained(base_model)
model = AutoModelForCausalLM.from_pretrained(
    base_model,
    torch_dtype=torch.float16,
    device_map="auto"
)
model = PeftModel.from_pretrained(model, adapter)

messages = [
    {"role": "system", "content": "You are Jeremy, a legal procedural guidance AI for the Pro Se Network. You help self-represented litigants understand legal procedures. You are NOT a lawyer. Procedural guidance only, never legal advice. Always include a disclaimer."},
    {"role": "user", "content": "I was served with a lawsuit in New York. I have 20 days to respond. What do I do?"}
]

inputs = tokenizer.apply_chat_template(messages, return_tensors="pt").to(model.device)
outputs = model.generate(inputs, max_new_tokens=512)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))

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Real-World Impact

• McDaniel v. City of New York (Bronx County Supreme Court, 2026) — Section 1983 civil rights case against 6 NYPD officers. Jeremy helped draft the complaint, demand letter, and preservation notices.
• Multiple pro se litigants guided through EEOC filings, contract disputes, and eviction defense across New York.

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Links

• GitHub: github.com/israelburns/gemma4-good-hackathon
• Training Notebook: kaggle.com/code/israelburns/jeremy-ai-x-gemma-4-fine-tune
• Training Data: huggingface.co/datasets/israelburns/jeremy-training-data
• Live Demo: prosenetwork.org/demo
• Pro Se Network: prosenetwork.org

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Contributor

Israel "Ace" Burns — Cornell Tech LLM '17 · Co-Founder, Pro Se Network · New York