| import torch | |
| from safetensors.torch import load_file | |
| def load_model(path='model.safetensors'): | |
| return load_file(path) | |
| def atmost2of4(a, b, c, d, weights): | |
| inp = torch.tensor([float(a), float(b), float(c), float(d)]) | |
| return int((inp @ weights['neuron.weight'].T + weights['neuron.bias'] >= 0).item()) | |
| if __name__ == '__main__': | |
| w = load_model() | |
| for i in range(16): | |
| a, b, c, d = (i >> 3) & 1, (i >> 2) & 1, (i >> 1) & 1, i & 1 | |
| print(f'{a}{b}{c}{d} -> {atmost2of4(a, b, c, d, w)}') | |