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license: mit
tags:
- harmonic-gpt
- oscillator-dynamics
- clifford-algebra
- byte-level
- from-scratch
- monumental-systems
language: en
pipeline_tag: text-generation
---
# Wire-2M (H16 L8, multidomain)
WireNative 2M — multi-domain training (philosophy + code + science)
Part of the [Harmonic GPT](https://github.com/DavinciDreams/harmonic-gpt) research into oscillator-based neural computation.
## Architecture: WireNative
| Property | Value |
|----------|-------|
| Parameters | 2,376,024 |
| BPB | 0.0000 |
| Training step | 0 |
| n_harmonics | 32 |
| n_layers | 8 |
| n_groups | 7 |
| d_model | 448 |
| 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-2m-multidomain", "model.safetensors"))
config = json.load(open(hf_hub_download("MonumentalSystems/wire-2m-multidomain", "config.json")))
```
All operations are native Clifford algebra / harmonic oscillator dynamics — no softmax attention, no MLP, no ReLU.
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