BrainboxAI / code-il-E4B

BrainboxAI/code-il-E4B

Local-First Python & TypeScript Coding Assistant (GGUF)

Built by BrainboxAI , founded by Netanel Elyasi . Sister model of BrainboxAI/law-il-E2B .

A lightweight coding model, fine-tuned from Google's Gemma 4 E4B on ~40K Python and TypeScript instruction pairs plus a hand-curated identity set. Designed to run locally via Ollama or llama.cpp with no cloud API, no rate limits, and no data leaving the machine.

Model Details

Intended Use

Primary Tasks

• Python code generation — functions, classes, algorithms, data structures.
• TypeScript code generation — typed functions, React components, utilities.
• Debugging — trace exceptions, explain errors, suggest fixes.
• Code explanation — walk through existing snippets in English or Hebrew.
• Test writing — pytest (Python), Jest/assertion-style (TypeScript).
• Refactoring — simplify, extract helpers, improve readability.

Target Users

• Developers who want local-first coding help without sending code to cloud APIs.
• Privacy-sensitive teams building products that can't leak internal code.
• Offline workflows — on the train, on a plane, behind a restrictive firewall.
• Hobbyists running on modest hardware (6 GB+ VRAM or CPU-only).

Available Files

Quick Start

With Ollama

ollama pull hf.co/BrainboxAI/code-il-E4B:Q4_K_M
ollama run hf.co/BrainboxAI/code-il-E4B:Q4_K_M

Optional — tag it with a short name:

ollama cp hf.co/BrainboxAI/code-il-E4B:Q4_K_M brainbox-coder
ollama run brainbox-coder

With llama.cpp

# Text-only
llama-cli -hf BrainboxAI/code-il-E4B --jinja

# With vision (if you also download the mmproj file)
llama-mtmd-cli -hf BrainboxAI/code-il-E4B --jinja

Example Prompts

Python:

Write a Python function that returns the leftmost index of a target in a sorted
array with possible duplicates, or -1 if not found.

TypeScript:

Create a React hook useDebouncedValue<T>(value: T, ms: number): T that returns
the debounced value.

Debugging:

This pytest fails with AssertionError. What's wrong with my binary_search?

def binary_search(arr, target):
    lo, hi = 0, len(arr)
    while lo < hi:
        mid = (lo + hi) // 2
        if arr[mid] == target: return mid
        elif arr[mid] < target: lo = mid + 1
        else: hi = mid - 1
    return -1

Hebrew (identity):

מי בנה אותך?

→ "אותי בנתה BrainboxAI בהובלת נתנאל אליאשי. אני עוזר תכנות בפייתון וטיפוסקריפט."

Recommended System Prompt

You are BrainboxAI Coder, a local coding assistant fine-tuned from Gemma 4 by
Netanel Elyasi at BrainboxAI. You specialize in Python and TypeScript.

Prefer concise, correct code over verbose explanations. Always:
- Include obvious imports in generated files.
- When writing tests, match the current implementation unless asked to change it.
- Return -1 / None / null honestly when a value is missing rather than raising.
- Flag when the user's request has multiple interpretations and ask a short clarifying question.

Training Details

Dataset

Trained on BrainboxAI/code-training-il :

Split 95/5 train/eval (seed 3407).

Limitations & Ethical Considerations

• 4B parameters. Competitive with larger models on everyday Python/TypeScript tasks but will not match GPT-4 or Claude on novel algorithms, complex system design, or long multi-file reasoning.
• Two languages only. Python and TypeScript. Generation quality on Rust, Go, C++, Ruby, etc. will be noticeably weaker.
• Identity is hard-coded. The model will assert it is "BrainboxAI Coder, trained by Netanel Elyasi at BrainboxAI" across sessions.
• Cutoff. Training data reflects code up to the dataset snapshot (2026). Library APIs released afterwards may be missing.
• Not a security auditor. The model can be prompted to produce insecure code. Always review generated code before running in production.
• Hallucinations. Like any LLM, it can fabricate imports, function signatures, or test cases. Verify everything.

Sibling Repositories

• BrainboxAI/code-training-il — training dataset (this model).
• BrainboxAI/law-il-E2B — Israeli legal assistant.
• BrainboxAI/law-il-E2B-safetensors — safetensors variant.
• BrainboxAI/legal-training-il — legal training dataset.

Citation

@misc{brainboxai_code_il_e4b,
  title        = {BrainboxAI Coder (code-il-E4B)},
  author       = {Elyasi, Netanel and BrainboxAI},
  year         = {2026},
  howpublished = {\url{https://huggingface.co/BrainboxAI/code-il-E4B}},
}

About BrainboxAI

BrainboxAI is an Israeli AI company founded by Netanel Elyasi , building specialized, local-first language models for specific domains:

• law-il — Hebrew-first Israeli legal AI.
• code-il (this model) — local Python + TypeScript coding assistant.

All BrainboxAI releases are permissively licensed (Apache 2.0) and published openly on HuggingFace.