---
license: apache-2.0
language:
  - en
tags:
  - ngari
  - sovereign-ai
  - edge-ai
  - qwen2.5
  - lora
base_model: Qwen/Qwen2.5-1.5B-Instruct
---

# NGARi Tool — Tool-Calling 1.5B

1.5B tool-calling model: Qwen2.5-1.5B-Instruct + tool-format LoRA. 100% tool detection / name / params validity on the NGARi tool-format eval (20 examples). Serves as the NGARi agent tool-mode model in production.

## Provenance (verified Aug 3, 2026)

| Attribute | Value |
|-----------|-------|
| Base model | `Qwen/Qwen2.5-1.5B-Instruct` (Apache 2.0) — pinned in `adapter_config.json` |
| LoRA | rank 32, alpha 64, dropout 0.05, all linear projections |
| Synthetic data teacher | `qwen3:8b` |
| License | Apache 2.0 (NGARi-authored artifacts) |
| Hardware validated | aarch64 / NVIDIA Jetson AGX Orin, 8GB RAM, air-gap verified |

> Note: Google Gemma models were **served only** on NGARi hardware and were never used in NGARi training. All training used the Apache-2.0 Qwen2.5 lineage.

## Evaluation

### ngari-tool-stable_tool_eval.json

```json
{
  "model": "ngari-tool:stable",
  "num_examples": 20,
  "total_examples": 20,
  "tool_detection_rate": 1.0,
  "tool_name_accuracy": 1.0,
  "params_validity_rate": 1.0,
  "tool_detected": 20,
  "name_correct": 20,
  "params_valid": 20,
  "avg_latency_sec": 3.17,
  "total_time_sec": 63.4
}
```

## Files

| File | Purpose |
|------|---------|
| `model-*.safetensors` (+ config) | Merged full model — use with Transformers |
| `adapter_model.safetensors` | PEFT LoRA adapter — apply on the base |
| `*-q4_K_M.gguf` / `*-f16.gguf` | GGUF — use with Ollama / llama.cpp |

## Usage

```bash
# Ollama (GGUF)
ollama create ngariai/ngari-tool:q4_K_M -f Modelfile

# Transformers (merged)
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("ngariai/ngari-tool")

# PEFT adapter (apply on base)
from peft import PeftModel
base = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-1.5B-Instruct")
adapter = PeftModel.from_pretrained(base, "ngariai/ngari-tool")
```

## Sovereign AI

Trained and verified on user-owned edge hardware with zero cloud dependency. Part of the NGARi Sovereign Business Operating System (NS-BOS) — see https://github.com/ngariai/ns-bos-kernel for the Apache 2.0 kernel.