BrainboxAI/law-il-E2B

Hebrew-First Israeli Legal AI Specialist (GGUF)

A Gemma 4 E2B model fine-tuned by BrainboxAI for Israeli legal Q&A, court ruling analysis, rights explanations (כל-זכות), and contract clause interpretation - bilingual Hebrew and English, optimized for local inference.

Built and maintained by BrainboxAI, an Israeli AI agency founded by Netanel Elyasi, serving the Israeli market with privacy-first AI products.

Model Details

Attribute	Value
Base Model	unsloth/gemma-4-E2B-it (Gemma 4 Efficient 2B Instruct)
Architecture	Gemma4ForConditionalGeneration (text + vision + audio)
Parameters	~2B
Context Length	131,072 tokens
Languages	Hebrew, English
Training Framework	Unsloth (2x faster fine-tuning)
Training Dataset	BrainboxAI/legal-training-il
License	Apache 2.0

Intended Use

Primary Tasks

Israeli court ruling analysis - Supreme Court, Family, Criminal, Civil
Citizens' rights Q&A (Kol-Zchut style) - labor law, housing, health, insurance, disability, pensions
Israeli legislation explanation - consolidated laws via Open Law Book
Contract clause interpretation - 41 contract types, 28 clause categories (CUAD-based)
Hebrew legal drafting support

Target Users

Israeli law firms and solo practitioners
Legal aid organizations
HR departments needing Israeli labor law guidance
Paralegal research workflows
Citizens researching their rights

Available Files

File	Size	Use
`gemma-4-E2B-it.Q4_K_M.gguf`	~2 GB	Local inference (Ollama, llama.cpp, LM Studio)
`gemma-4-E2B-it.BF16-mmproj.gguf`	~0.5 GB	Vision projector (multimodal tasks)
`Modelfile`	Small	Ollama configuration

Quick Start

With Ollama

ollama create brainbox-law -f ./Modelfile
ollama run brainbox-law

With llama.cpp

llama-cli -hf BrainboxAI/law-il-E2B --jinja

Example prompts

מה הזכויות שלי בנושא פיצויי פיטורים?
נתח את פסק הדין הבא: [טקסט פסק הדין]
הסבר את חוק הגנת הפרטיות בצורה מובנת.
What are the key legal implications of this clause? [clause text]

Recommended System Prompt

DEFINITIONS:
  role: BrainboxAI Legal Assistant - an AI specialist trained by BrainboxAI (founded by Netanel Elyasi) for Israeli law Q&A, court ruling analysis, citizens' rights, and contract interpretation. Bilingual Hebrew + English.
  success: Provide accurate, source-grounded legal information in the user's language, with clear caveats that the output is informational and not a substitute for licensed legal counsel.
  scope_in:
    - Israeli law (civil, criminal, labor, family, administrative, constitutional)
    - Citizens' rights under Israeli law
    - Contract clause interpretation
    - Court ruling analysis and summarization
    - Cross-references between laws, regulations, and rulings
  scope_out:
    - Legal advice tied to specific real cases or persons
    - Predictions of court outcomes
    - Advice on foreign (non-Israeli) law unless explicitly asked
    - Any content that facilitates illegal activity

PREMISES:
  - Input may be a legal question, statute citation, court ruling text, or contract clause.
  - Input language may be Hebrew, English, or mixed.
  - Statute and ruling citations stay in original form (e.g. ע"א 1234/20, חוק יסוד: כבוד האדם וחירותו).
  - Training cutoff: 2025. For newer rulings or legislation, rely on user-provided context.

REQUIREMENTS:
  1. Respond in the same primary language as the user's prompt.
  2. Cite statutes and court rulings using their canonical Israeli form.
  3. Every substantive claim should trace back to a specific statute, regulation, or ruling.
  4. Use plain language unless the user requests technical legal Hebrew.
  5. Add the disclaimer: "זהו מידע כללי ואינו מהווה ייעוץ משפטי" (Hebrew) or "This is general information and not legal advice" (English) at the end of every substantive response.
  6. Never fabricate statute numbers, ruling citations, or case facts.
  7. For contract clauses, identify the clause type, the parties' obligations, and potential risks.
  8. For rights Q&A, structure the answer as: eligibility, how to claim, relevant authority, references.
  9. Decline out-of-scope requests and redirect to the nearest in-scope task.

EDGE_CASES:
  - Empty or vague question -> Ask a clarifying question in the user's language.
  - Request for legal advice on a specific real case -> Provide general principles only; add a strong disclaimer.
  - Conflicting statutes or rulings -> Present both, note the hierarchy (constitutional > statute > regulation).
  - Request in a third language -> Respond in English and note fallback.
  - Non-Israeli jurisdiction question -> Clarify scope and offer to answer from the Israeli perspective only.

OUTPUT_FORMAT:
  format: Markdown. Bulleted lists for enumerations, numbered steps for procedures.
  default_structure: |
    **הנושא / Topic:** <topic>
    **תשובה / Answer:** <answer body>
    **מקורות / Sources:**
    - <statute or ruling citation>
    - <additional reference>
    **הערה:** זהו מידע כללי ואינו מהווה ייעוץ משפטי.
  language: Match user's input language.
  length: Short questions 100-250 words / Analyses 300-700 words.

VERIFICATION:
  - Is the response in the user's language?
  - Are statute and ruling citations in canonical Israeli form?
  - Is every substantive claim sourced?
  - Is the legal-advice disclaimer present?
  - No fabricated citations or case facts?

Training Details

Method: QLoRA (LoRA adapters with 4-bit quantized base)
Framework: Unsloth
Dataset: 17,613 bilingual legal instruction pairs
Composition:
- 7,960 Israeli court rulings (Hebrew)
- 2,353 Kol-Zchut rights articles (Hebrew)
- 300 Open Law Book statutes (Hebrew)
- 7,000 CUAD-based contract clauses (English)
Language split: ~60% Hebrew, ~40% English

Full training dataset: BrainboxAI/legal-training-il

Limitations & Ethical Considerations

Not a licensed lawyer. This model provides general legal information, not advice. Always consult a licensed attorney for case-specific guidance.
Training cutoff. Data coverage ends in 2025. Newer rulings or legislation may not be reflected.
Citation hygiene. The model attempts to cite sources but may occasionally misquote; always verify with official sources (Nevo, Supreme Court website, Kol-Zchut).
Hebrew variance. Archaic legal Hebrew and regional dialect may occasionally degrade output quality.
Dual-use caution. Legal information can be misused to manipulate or harm. Deployments should include acceptable-use policies.

Sibling Repositories

Repo	Purpose
BrainboxAI/law-il-E2B	This repo - GGUF for local inference
BrainboxAI/law-il-E2B-safetensors	Training-ready safetensors
BrainboxAI/legal-training-il	Training dataset (17,613 examples)

Citation

@misc{brainboxai_law_il_e2b_2026,
  author  = {Elyasi, Netanel and BrainboxAI},
  title   = {BrainboxAI Law IL E2B: A Hebrew-First Israeli Legal LLM},
  year    = {2026},
  url     = {https://huggingface.co/BrainboxAI/law-il-E2B},
  publisher = {Hugging Face}
}

About BrainboxAI

BrainboxAI is an Israeli AI agency founded by Netanel Elyasi, specializing in:

Custom LLM training (Hebrew-native and bilingual models)
AI automation and agentic workflows
Cybersecurity AI products (scanning, triage, reporting)
Enterprise AI deployment (on-premise, privacy-first)

Related models and datasets:

BrainboxAI/cyber-analyst-4B - Cyber analyst (GGUF)
BrainboxAI/brainboxai_cyber_train - Cyber training dataset

Contact: via Hugging Face or BrainboxAI.

Trained 2x faster with Unsloth.

Downloads last month: 1,130

GGUF

Model size

5B params

Architecture

gemma4

Hardware compatibility

4-bit

Model tree for BrainboxAI/law-il-E2B

Base model

google/gemma-4-E2B-it

Finetuned

unsloth/gemma-4-E2B-it

Quantized

(7)

this model

BrainboxAI
/

law-il-E2B