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threshold-parity4
phanerozoic/threshold-parity4
threshold-parity4 is a machine learning model from phanerozoic. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
4-bit parity function. Outputs 1 if odd number of inputs are high.
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.py2.8 KB · 48%
At a glance
- License
- mit
- Access
- Public
- Created
- Jan 23, 2026
- Updated
- Jan 23, 2026
- SHA
- 47290518
Model card
From the Hugging Face model README
threshold-parity4
4-bit parity function. Outputs 1 if odd number of inputs are high.
Function
parity4(a, b, c, d) = a XOR b XOR c XOR d
Architecture
Tree structure: parity(a,b,c,d) = XOR(XOR(a,b), XOR(c,d))
Three XOR2 gates, each using OR-NAND-AND structure:
- xor_ab: XOR(a, b) - parallel with xor_cd
- xor_cd: XOR(c, d) - parallel with xor_ab
- xor_final: XOR(xor_ab, xor_cd)
Layer structure:
- or1, nand1 (a,b) and or2, nand2 (c,d) in parallel
- and1 (xor_ab) and and2 (xor_cd)
- or3, nand3 (on xor outputs)
- and3 (final output)
Parameters
| Inputs | 4 |
| Outputs | 1 |
| Neurons | 9 |
| Layers | 4 |
| Parameters | 27 |
| Magnitude | 30 |
Usage
from safetensors.torch import load_file
w = load_file('model.safetensors')
def xor2(a, b, prefix):
or_out = int(a * w[f'{prefix}.or.weight'][0] + b * w[f'{prefix}.or.weight'][1] + w[f'{prefix}.or.bias'] >= 0)
nand_out = int(a * w[f'{prefix}.nand.weight'][0] + b * w[f'{prefix}.nand.weight'][1] + w[f'{prefix}.nand.bias'] >= 0)
return int(or_out * w[f'{prefix}.and.weight'][0] + nand_out * w[f'{prefix}.and.weight'][1] + w[f'{prefix}.and.bias'] >= 0)
def parity4(a, b, c, d):
return xor2(xor2(a, b, 'xor_ab'), xor2(c, d, 'xor_cd'), 'xor_final')
print(parity4(1, 0, 1, 0)) # 0 (even)
print(parity4(1, 1, 1, 0)) # 1 (odd)
License
MIT
- License
- mit
- Created
- Jan 23, 2026
- Updated
- Jan 23, 2026