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threshold-2to4decoder
phanerozoic/threshold-2to4decoder
threshold-2to4decoder 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.
2-to-4 binary decoder. Converts 2-bit input to one-hot 4-bit output.
All-time downloads
53
Public
Parameters
12
Likes
0
Public
Repo makeup
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.py1.7 KB · 47%
At a glance
- License
- mit
- Access
- Public
- Created
- Jan 23, 2026
- Updated
- Jan 24, 2026
- SHA
- 67df09a2
Model card
From the Hugging Face model README
threshold-2to4decoder
2-to-4 binary decoder. Converts 2-bit input to one-hot 4-bit output.
Function
decode(A1, A0) -> [Y0, Y1, Y2, Y3]
Yi = 1 iff input = i
Truth Table
| A1 | A0 | Y0 | Y1 | Y2 | Y3 |
|---|---|---|---|---|---|
| 0 | 0 | 1 | 0 | 0 | 0 |
| 0 | 1 | 0 | 1 | 0 | 0 |
| 1 | 0 | 0 | 0 | 1 | 0 |
| 1 | 1 | 0 | 0 | 0 | 1 |
Architecture
Single layer with 4 neurons. Each Yi matches pattern i.
| Output | Weights [A1, A0] | Bias |
|---|---|---|
| Y0 | [-1, -1] | 0 |
| Y1 | [-1, +1] | -1 |
| Y2 | [+1, -1] | -1 |
| Y3 | [+1, +1] | -2 |
Parameters
| Inputs | 2 |
| Outputs | 4 |
| Neurons | 4 |
| Layers | 1 |
| Parameters | 12 |
| Magnitude | 12 |
Usage
from safetensors.torch import load_file
import torch
w = load_file('model.safetensors')
def decode2to4(a1, a0):
inp = torch.tensor([float(a1), float(a0)])
return [int((inp * w[f'y{i}.weight']).sum() + w[f'y{i}.bias'] >= 0) for i in range(4)]
print(decode2to4(1, 0)) # [0, 0, 1, 0] - input 2
License
MIT
- License
- mit
- Created
- Jan 23, 2026
- Updated
- Jan 24, 2026