model.py

import torch
from safetensors.torch import load_file

def load_model(path='model.safetensors'):
    return load_file(path)

def lte(a, b, weights):
    inp = torch.tensor([float(a), float(b)])
    return int((inp @ weights['neuron.weight'].T + weights['neuron.bias'] >= 0).item())

if __name__ == '__main__':
    w = load_model()
    print('lessthanorequal truth table:')
    for a in [0, 1]:
        for b in [0, 1]:
            print(f'  {a} <= {b} -> {lte(a, b, w)}')