phanerozoic / threshold-jk-flipflop

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Total runs: 8
24-hour runs: 0
7-day runs: -7
30-day runs: 4
Model's Last Updated: January 24 2026

Introduction of threshold-jk-flipflop

Model Details of threshold-jk-flipflop

threshold-jk-flipflop

JK flip-flop next-state logic as threshold circuit. Most versatile flip-flop with Set, Reset, Hold, and Toggle modes.

Circuit
J      ──┐
K      ──┼──► JK-FF ──┬──► Q
Q_prev ──┘           └──► Qn
Truth Table
J K Q_prev Q Qn Mode
0 0 0 0 1 Hold
0 0 1 1 0 Hold
0 1 X 0 1 Reset
1 0 X 1 0 Set
1 1 0 1 0 Toggle
1 1 1 0 1 Toggle
Modes
J=0, K=0: Hold    - Q stays same
J=0, K=1: Reset   - Q becomes 0
J=1, K=0: Set     - Q becomes 1
J=1, K=1: Toggle  - Q flips
Logic
Q  = J·~Q_prev + ~K·Q_prev
Qn = ~J·~Q_prev + K·Q_prev
Architecture
Component Neurons
Input inversions 4
AND gates 4
OR outputs 2
Passthroughs 2

Total: 12 neurons, 42 parameters, 3 layers

Advantage Over SR

Unlike SR flip-flop, JK has no invalid state. When both inputs are high, it toggles instead of producing undefined behavior.

Usage
from safetensors.torch import load_file

w = load_file('model.safetensors')

# Counter using toggle mode:
q = 0
for _ in range(4):
    q_next = compute(j=1, k=1, q_prev=q, w)
    q = q_next  # q toggles: 0,1,0,1,...
Files
threshold-jk-flipflop/
├── model.safetensors
├── create_safetensors.py
├── config.json
└── README.md
License

MIT

Runs of phanerozoic threshold-jk-flipflop on huggingface.co

8
Total runs
0
24-hour runs
-4
3-day runs
-7
7-day runs
4
30-day runs

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threshold-jk-flipflop install

threshold-jk-flipflop is an open source model from GitHub that offers a free installation service, and any user can find threshold-jk-flipflop on GitHub to install. At the same time, huggingface.co provides the effect of threshold-jk-flipflop install, users can directly use threshold-jk-flipflop installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

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Updated:September 26 2026