| import torch | |
| from safetensors.torch import load_file | |
| def load_model(path='model.safetensors'): | |
| return load_file(path) | |
| def nand3(a, b, c, weights): | |
| """3-input NAND gate.""" | |
| inp = torch.tensor([float(a), float(b), float(c)]) | |
| return int((inp * weights['weight']).sum() + weights['bias'] >= 0) | |
| if __name__ == '__main__': | |
| w = load_model() | |
| print('3-input NAND truth table:') | |
| for a in [0, 1]: | |
| for b in [0, 1]: | |
| for c in [0, 1]: | |
| print(f'NAND({a},{b},{c}) = {nand3(a, b, c, w)}') | |