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import torch
from safetensors.torch import load_file
def load_model(path='model.safetensors'):
return load_file(path)
def signbit4(a3, a2, a1, a0, weights):
"""Returns sign bit (MSB) of 4-bit number. 1 = negative in 2's complement."""
inp = torch.tensor([float(a3), float(a2), float(a1), float(a0)])
return int((inp @ weights['neuron.weight'].T + weights['neuron.bias'] >= 0).item())
if __name__ == '__main__':
w = load_model()
print('signbit4 truth table:')
for i in range(16):
a3, a2, a1, a0 = (i >> 3) & 1, (i >> 2) & 1, (i >> 1) & 1, i & 1
result = signbit4(a3, a2, a1, a0, w)
signed_val = i if i < 8 else i - 16
print(f' {a3}{a2}{a1}{a0} (unsigned={i:2d}, signed={signed_val:+3d}) -> sign={result}')
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