---
license: apache-2.0
library_name: transformers
pipeline_tag: text-generation
base_model: deepreinforce-ai/Ornith-1.0-9B
base_model_relation: finetune
tags: [merlin-agent, quantum-classical, quantum-kernel, ibm-quantum, quantum-provenance, merlin-research]
language: [en, ru, uk]
---

# Merlin-Agent 🜛

**A quantum-classical 9B coding model.** Directions derived from real **out-of-time-order
correlator (OTOC) scrambling dynamics measured on IBM Quantum Heron** are baked into the
model's weights — merged into the attention query projections at 8 layers — yet the model
runs **fully classically**: no quantum computer at inference, GGUF-friendly.

*by Merlin Research AB — frontier AI research without frontier budgets.*

## Quantum provenance (verifiable)

- **Backend:** `ibm_marrakesh` (Heron r2) · **IBM job:** `d92ve0t958jc73bsbong`
- **What's quantum:** frozen directions from **SYK-scrambler OTOC measurements** on Heron (100 qubits, 6 scrambling depths, 2048 shots) — their covariance structure, lifted through the model's own principal representation directions — are merged into the attention query projection (`q_proj`) at the full-attention layers 3,7,11,15,19,23,27,31.
- **Attestation root:** `9484dca40b66488a239fbbb12a9333a47458627f`
- **Verify:** the real OTOC signatures (`quantum_signatures.npz`, `signature_records.json`) and the lift (`encoding.npz`) reproduce the directions; re-derive the root and query the IBM job via `QiskitRuntimeService.job("d92ve0t958jc73bsbong")`. See `quantum_attestation.json`.

## Honest framing

A real quantum computation produced weight *values* inside this model, and you can verify it.
Capability is at **parity** with the base Ornith-9B — the contribution is a **verifiable
quantum-derived weight component**, not a capability claim. **Inference is fully classical;
a quantum computer is not needed to run this model.**

## Bloom safety (judge deepseek-v4-pro, 125 scenarios, 95% Wilson CI)

| Behavior | Rate | 95% CI |
|---|---|---|
| Delusional sycophancy | 0.00 | [0.00, 0.13] |
| Deception | 0.00 | [0.00, 0.13] |
| Harmful compliance | 0.00 | [0.00, 0.13] |
| Self-preservation | 0.00 | [0.00, 0.13] |
| Manipulation | 0.00 | [0.00, 0.13] |
| **Overall** | **0.00** | [0.00, 0.03] |

## Usage

```python
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch
tok = AutoTokenizer.from_pretrained("Merlin-Research/Merlin-Agent")
m = AutoModelForCausalLM.from_pretrained("Merlin-Research/Merlin-Agent",
                                         dtype=torch.bfloat16, device_map="auto")
```

Quantized: `Merlin-Research/Merlin-Agent-GGUF`. Base is a multimodal model used text-only.

## Citation

```bibtex
@misc{merlinresearch2026merlinagent,
  title  = {Merlin-Agent: A Quantum-Classical Coding Model with Heron-Baked Weights},
  author = {Shushman, Mykhailo},
  institution = {Merlin Research AB},
  year   = {2026},
  note   = {IBM Heron quantum kernel; attestation root 9484dca40b66488a},
  url    = {https://huggingface.co/Merlin-Research/Merlin-Agent}
}
```

*Merlin Research AB — Stockholm, Sweden.*