metadata
license: cc0-1.0
base_model: mlx-community/Qwen2.5-Coder-7B-Instruct-4bit
tags:
- mlx
- cybersecurity
- nist
- security-controls
- compliance
- fine-tuned
language:
- en
HackIDLE-NIST-Coder v1.1 (MLX 4-bit)
The most comprehensive NIST cybersecurity model - Fine-tuned on 530,912 examples from 596 NIST publications.
Model Overview
This is an MLX-optimized 4-bit quantized model fine-tuned specifically for NIST cybersecurity expertise. Version 1.1 includes significant improvements over v1.0:
- +7,206 training examples (530,912 total)
- +28 new documents (596 NIST publications)
- CSWP series added: CSF 2.0, Zero Trust Architecture, Post-Quantum Cryptography
- Improved quality: Fixed 6,150 malformed DOI links
Training Results
- Training iterations: 1,000 (+ 200 checkpoint recovery)
- Best validation loss: 1.512 (12.5% improvement)
- Training loss: 1.420 (final)
- Trainable parameters: 11.5M (0.151% of 7.6B total)
- Training time: ~5 hours on M4 Max
Installation
pip install mlx-lm
Usage
from mlx_lm import load, generate
model, tokenizer = load("ethanolivertroy/HackIDLE-NIST-Coder-v1.1-MLX-4bit")
prompt = "What is Zero Trust Architecture according to NIST SP 800-207?"
response = generate(model, tokenizer, prompt=prompt, max_tokens=500)
print(response)
Other Formats
License
CC0 1.0 Universal (Public Domain) - All NIST publications are in the public domain.
Version: 1.1 Release Date: October 2025