This adapter is deprecated. Use odoom/nixpkgs-security-qwen-lora instead — Qwen 2.5 Coder 32B with multi-turn tool-calling, lower loss (0.54 vs 0.87), and higher accuracy (90% vs 80%).

What Changed

	v2 (this repo)	v3 (new repo)
Base model	Mistral 7B Instruct v0.2	Qwen 2.5 Coder 32B Instruct
Format	Single-turn (system/user/assistant)	Multi-turn tool-calling conversations
Loss	0.867	0.540
Token accuracy	80.5%	90.1%
Adapter size	160 MB	256 MB
Tool calling	Broken (`raw: true` disabled it)	Native Qwen 2.5 tool calling

Original Model Details (v2)

Base model: Mistral 7B Instruct v0.2
Method: QLoRA (4-bit NF4 quantization + LoRA rank 32)
Target: Cloudflare Workers AI @cf/mistral/mistral-7b-instruct-v0.2-lora
Adapter size: 160 MB
Training data: 586 complex security patches (version bumps filtered out)
Epochs: 3 (110 steps), ~61 minutes on NVIDIA L4

Training Metrics

Metric	Start	End
Loss	1.166	0.867
Token accuracy	74.6%	80.5%
Eval loss	—	0.924
Eval accuracy	—	78.4%

Changelog

v2 (2026-03-03): Retrained on filtered dataset — removed 763 version bump / hash-only examples.
v1 (2026-03-02): Initial training on 1,273 unfiltered examples.

odoom/nixpkgs-security-lora

nixpkgs-security-lora (Deprecated)

What Changed

Original Model Details (v2)

Training Metrics

Changelog

odoom/
nixpkgs-security-lora