Reference

Fine-tuned models

GNO ships a fine-tuned local expansion model trained on Apple Silicon with MLX LoRA.

GNO publishes a fine-tuned retrieval expansion model —gno-expansion-slim-retrieval-v1 — trained locally on Apple Silicon with MLX LoRA. It’s the default on fresh installs and benchmarks meaningfully above the base slim preset.

The numbers

• nDCG@10 0.925 on the canonical benchmark corpus
• Ask Recall@5 0.875 on the ask-style answer benchmark
• Shipped via Hugging Face, pulled on first run

Install it

gno models use slim-tuned
gno models pull

Train your own

The training harness lives in the main GNO repo under research/. It uses MLX LoRA for local fine-tuning and can export GGUF artifacts you can install via the Hugging-Face-backed custom preset format.

Benchmarks

Before promoting a model change, run the benchmark suite. See the benchmarks feature page for the full canonical corpora and the autonomous candidate search.

bun run eval:hybrid
bun run bench:code-embeddings --candidate bge-m3 --write