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threshold-minority3
phanerozoic/threshold-minority3
threshold-minority3 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.
3-input minority gate. Outputs 1 when at most 1 of 3 inputs is high. Complement of majority3.
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.py1.3 KB · 48%
At a glance
- License
- mit
- Access
- Public
- Created
- Jan 23, 2026
- Updated
- Jan 23, 2026
- SHA
- 1c9aeb5f
Model card
From the Hugging Face model README
threshold-minority3
3-input minority gate. Outputs 1 when at most 1 of 3 inputs is high. Complement of majority3.
Function
minority3(a, b, c) = 1 if (a + b + c) <= 1, else 0
Truth Table
| a | b | c | sum | out |
|---|---|---|---|---|
| 0 | 0 | 0 | 0 | 1 |
| 0 | 0 | 1 | 1 | 1 |
| 0 | 1 | 0 | 1 | 1 |
| 0 | 1 | 1 | 2 | 0 |
| 1 | 0 | 0 | 1 | 1 |
| 1 | 0 | 1 | 2 | 0 |
| 1 | 1 | 0 | 2 | 0 |
| 1 | 1 | 1 | 3 | 0 |
Architecture
Single neuron: weights [-1, -1, -1], bias 1
Fires when: -a - b - c + 1 >= 0, i.e., sum <= 1
Parameters
| Inputs | 3 |
| Outputs | 1 |
| Neurons | 1 |
| Layers | 1 |
| Parameters | 4 |
| Magnitude | 4 |
Usage
from safetensors.torch import load_file
import torch
w = load_file('model.safetensors')
def minority3(a, b, c):
inp = torch.tensor([float(a), float(b), float(c)])
return int((inp @ w['neuron.weight'].T + w['neuron.bias'] >= 0).item())
print(minority3(0, 0, 1)) # 1
print(minority3(0, 1, 1)) # 0
License
MIT
- License
- mit
- Created
- Jan 23, 2026
- Updated
- Jan 23, 2026