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import torch
from safetensors.torch import load_file
def load_model(path='model.safetensors'):
return load_file(path)
def isone4(a3, a2, a1, a0, weights):
"""Returns 1 if 4-bit input equals 1 (0001), else 0"""
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('isone4 truth table:')
for i in range(16):
a3, a2, a1, a0 = (i >> 3) & 1, (i >> 2) & 1, (i >> 1) & 1, i & 1
result = isone4(a3, a2, a1, a0, w)
marker = ' <-- ONE' if result else ''
print(f' {a3}{a2}{a1}{a0} (={i:2d}) -> {result}{marker}')
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