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import torch
from safetensors.torch import load_file
def load_model(path='model.safetensors'):
return load_file(path)
def majority7(a, b, c, d, e, f, g, weights):
inp = torch.tensor([float(a), float(b), float(c), float(d), float(e), float(f), float(g)])
return int((inp @ weights['neuron.weight'].T + weights['neuron.bias'] >= 0).item())
if __name__ == '__main__':
w = load_model()
print('majority7 sample outputs:')
print(f' 0000000 -> {majority7(0,0,0,0,0,0,0,w)}')
print(f' 0000111 -> {majority7(0,0,0,0,1,1,1,w)}')
print(f' 0001111 -> {majority7(0,0,0,1,1,1,1,w)}')
print(f' 1111111 -> {majority7(1,1,1,1,1,1,1,w)}')
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