model.py

import torch
from safetensors.torch import load_file

def load_model(path='model.safetensors'):
    return load_file(path)

def decode2to4(a1, a0, weights):
    inp = torch.tensor([float(a1), float(a0)])
    return [int((inp * weights[f'y{i}.weight']).sum() + weights[f'y{i}.bias'] >= 0) for i in range(4)]

if __name__ == '__main__':
    w = load_model()
    print('2-to-4 Decoder:')
    for val in range(4):
        a1, a0 = (val >> 1) & 1, val & 1
        result = decode2to4(a1, a0, w)
        print(f'  {val} ({a1}{a0}) -> {"".join(map(str, result))}')