Use it as a helper. Do not treat it as a source of truth for exact control names, RMF step lists, or reference-architecture component names without checking the source publication.

What went into v1.1

Version 1.1 was trained on 530,912 examples from 596 NIST publications.

Compared with the first release, v1.1 added:

7,206 training examples
28 additional NIST documents
CSWP coverage, including CSF 2.0, Zero Trust, and Post-Quantum Cryptography material
cleanup for 6,150 malformed DOI links
removal of known broken-link markers in the training corpus

Training dataset:

ethanolivertroy/nist-cybersecurity-training

Current eval status

I ran a small local smoke eval on April 22, 2026 against etgohome/hackidle-nist-coder:latest. In that local Ollama install, latest matched the v1.1 line.

Result: 1/5 cases passed.

The model stayed in-domain and handled a rough FIPS 140-2 vs. FIPS 140-3 comparison. It still missed exact grounding on:

SP 800-207 reference-architecture component names
the full SP 800-37 Rev. 2 RMF sequence
the exact CM-6 control name and description
stronger publication selection and logging/audit grounding for a contractor remote-access planning prompt

That is the important limitation. The model can sound close while still being wrong on exact NIST structure.

Good uses

This model is useful for:

brainstorming where to start in NIST
drafting first-pass explanations
surfacing likely document families
turning NIST-flavored questions into something a human can verify
local experimentation with domain fine-tuning on Apple Silicon

It is not reliable enough yet for:

exact control names
exact framework step ordering
exact reference-architecture component naming
answers that need source-level correctness on the first pass

Available quantizations

Quantization	Approx. size	Use case
F16	14 GB	Full precision reference build
Q8_0	7.5 GB	Higher quality local inference
Q5_K_M	5.1 GB	Balanced size and quality
Q4_K_M	4.4 GB	Small local default for most machines

Start with Q4_K_M unless you have a reason to use a larger file.

Run with Ollama

bash

ollama pull etgohome/hackidle-nist-coder:v1.1
ollama run etgohome/hackidle-nist-coder:v1.1 "Which NIST docs would you read before drafting a zero trust migration plan?"

Run with llama.cpp

bash

git clone https://github.com/ggerganov/llama.cpp
cd llama.cpp
make

wget https://huggingface.co/ethanolivertroy/HackIDLE-NIST-Coder-v1.1-GGUF/resolve/main/hackidle-nist-coder-v1.1-q4_k_m.gguf

./llama-cli \
  -m hackidle-nist-coder-v1.1-q4_k_m.gguf \
  -p "Which NIST docs would you start with for contractor remote access?" \
  -n 500

Other formats

MLX: ethanolivertroy/HackIDLE-NIST-Coder-v1.1-MLX-4bit
Ollama: etgohome/hackidle-nist-coder

License

The base model is Qwen2.5-Coder-7B-Instruct, released under Apache 2.0. The NIST source publications used for the dataset are public domain U.S. government works. This model card uses Apache 2.0 for the model artifact and documents the NIST data source separately.

Citation

bibtex

@misc{hackidle_nist_coder_v11_gguf,
  title = {HackIDLE-NIST-Coder v1.1 GGUF},
  author = {Troy, Ethan Oliver},
  year = {2025},
  version = {1.1},
  url = {https://huggingface.co/ethanolivertroy/HackIDLE-NIST-Coder-v1.1-GGUF}
}