Wire-9M (H64 L8)

WireNative 9M โ€” 64 harmonics, 8 layers, selected BPB checkpoint.

Part of the 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

This repository contains weights and configuration for research inspection. It does not currently bundle a standalone transformers runtime.

import json

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")))

Sequence mechanism

This is an attention-free oscillator model. Its sequence mixing uses native Clifford algebra and harmonic dynamics rather than softmax attention, an attention KV cache, MLPs, or ReLU activations. The reported BPB is a run-selection diagnostic and should not be compared across corpora or evaluation protocols without reproducing the original setup.

Downloads last month
30
Safetensors
Model size
8.89M params
Tensor type
F32
ยท
Inference Providers NEW
This model isn't deployed by any Inference Provider. ๐Ÿ™‹ Ask for provider support

Space using MonumentalSystems/wire-9m-best 1

Collection including MonumentalSystems/wire-9m-best