Add Wire-9M (H32 L8) checkpoint (step 5000, bpb 3.0866)

README.md

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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-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.

config.json

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+{
+  "architecture": "WireNative",
+  "n_groups": 7,
+  "n_harmonics": 64,
+  "n_layers": 8,
+  "d_model": 896,
+  "n_kan_coeffs": 4,
+  "vocab_size": 256,
+  "seq_len": 256,
+  "training": {
+    "step": 5000,
+    "bpb": 3.086578
+  }
+}

model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:1537f4c5aac0d2ba04034f22919c9a028653d413e5bba791d4ffc5c67d326b8b
+size 35599096