---
license: mit
tags:
  - harmonic-gpt
  - oscillator-dynamics
  - clifford-algebra
  - byte-level
  - from-scratch
  - monumental-systems
language: en
pipeline_tag: text-generation
---

# Wire-9M (H32 L8)

WireNative 9M — n_harmonics=32, 8 layers, best BPB checkpoint

Part of the [Harmonic GPT](https://github.com/DavinciDreams/harmonic-gpt) research into oscillator-based neural computation.

## Architecture: WireNative

| Property | Value |
|----------|-------|
| Parameters | 8,894,520 |
| BPB | 3.0866 |
| Training step | 5,000 |
| n_harmonics | 64 |
| n_layers | 8 |
| n_groups | 7 |
| d_model | 896 |
| Vocab | 256 (raw bytes) |

## Usage

```python
from huggingface_hub import hf_hub_download
from safetensors.torch import load_file

weights = load_file(hf_hub_download("MonumentalSystems/wire-9m-best", "model.safetensors"))
config = json.load(open(hf_hub_download("MonumentalSystems/wire-9m-best", "config.json")))
```

All operations are native Clifford algebra / harmonic oscillator dynamics — no softmax attention, no MLP, no ReLU.