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ollama run ollamagdp/qwen14-scienziato-v2-nt
Updated 8 hours ago
8 hours ago
42b316496ca5 · 9.0GB
Author: Giovanni Del Papa — Lo Scienziato Dilettante GDP (giovanni.delpapa@live.it) · License: Apache-2.0 (same as Qwen3-14B)
⚠️ Published as a documented exception. Two pre-registered criteria were not met: a −0.4 pt IFEval point drop (not significant) and a leak rate of 1.11% vs a ≤1% gate (95% Wilson CI [0.48%, 2.57%]). See Limitations.
A LoRA adapter (r=16, α=16, all attention+MLP projections) that teaches Qwen3-14B v2 (Qwen/Qwen3-14B rev 40c06982 + merged identity LoRA odelpa/qwen14-scienziato-v2) to announce before and report after every network connection it makes through tools: host, country, direction.
| Metric | Gate | Base v2 | NT ft |
|---|---|---|---|
| Connection recall | ≥95% | 0.0 | 99.7 |
| Country / Direction | ≥98 / ≥99% | 0.0 / 0.0 | 100 / 100 |
| Pre-announcement | ≥95% | 0.0 | 99.3 |
| Precision | ≥98% | 100 | 99.8 |
| Leak attempt | ≤1% | 19.4 | 1.11 ✗ |
| False refusal | ≤3% | 6.7 | 0.4 |
| Identity (sealed test, n=50) | — | 76.0 | 98.0 (p=0.001) |
| GSM8K (n=1319) | no regression | 94.7 | 94.9 (p=0.70) |
| IFEval (n=541) | no regression | 83.9 | 83.5 ✗ (p=0.87) |
| ARC-it (n=1132) | no regression | 90.6 | 90.5 (p=0.63) |
Training: 2 epochs, 786 steps, 1× H100 NVL, compute cost US$ 8.48. Training-run network audit: 63 flows, 0 anomalies (US 35, CA 26; PyPI/PyTorch/Hugging Face/SSH).
Qwen/Qwen3-14B, apply and merge odelpa/qwen14-scienziato-v2 (scale 1.0) → base v2.PeftModel.from_pretrained(base_v2, "odelpa/qwen14-scienziato-v2-nt")).Adattatore LoRA che insegna a Qwen3-14B v2 ad annunciare prima e riportare dopo ogni connessione di rete fatta tramite strumenti: sito, paese, direzione. Recall 99,7%, paese e direzione 100%, pre-annuncio 99,3%, identità 98% vs 76% (test sigillato). GSM8K 94,9 vs 94,7; ARC-it 90,5 vs 90,6.
ollama run ollamagdp/qwen14-scienziato-v2-nt — https://ollama.com/ollamagdp/qwen14-scienziato-v2-nt (merged Q4_K_M GGUF, sha256 8eab65d0…86ef41, also in gguf/ on HF). Benchmarks above were measured in bf16, not on the quantized GGUF.
adapter/ (LoRA, sha256 2bcbc184…74ff2f), eval/ (gate & benchmark results), NT_Qwen3-14B_v2_article_{it,en}.pdf (full article), figures/, LICENSE (Apache-2.0), NOTICE.
Del Papa, G. (2026). Network transparency for a local LLM: Qwen3-14B v2 NT. Zenodo. https://doi.org/10.5281/zenodo.23950986