phanerozoic / threshold-t-flipflop

huggingface.co
Total runs: 5
24-hour runs: 0
7-day runs: -6
30-day runs: -2
Model's Last Updated: January 24 2026

Introduction of threshold-t-flipflop

Model Details of threshold-t-flipflop

threshold-t-flipflop

T flip-flop (toggle) next-state logic as threshold circuit.

Circuit
T ───────┐
Q_prev ──┴──► T-FF ──┬──► Q
                    └──► Qn
Modes
  • T=0 (Hold): Q stays same
  • T=1 (Toggle): Q flips
Truth Table
T Q_prev Q Qn Mode
0 0 0 1 Hold
0 1 1 0 Hold
1 0 1 0 Toggle
1 1 0 1 Toggle
Logic
Q  = T XOR Q_prev
Qn = T XNOR Q_prev

XOR is not linearly separable (the classic Minsky/Papert result), requiring 2 layers.

Architecture
    T      Q_prev
    │        │
    ├────┬───┤
    │    │   │
    ▼    ▼   ▼
  ┌────┬────┬────┬────┐
  │ OR │NAND│NOR │AND │   Layer 1
  └────┴────┴────┴────┘
    │    │    │    │
    └─┬──┘    └─┬──┘
      │         │
      ▼         ▼
   ┌─────┐   ┌─────┐
   │ AND │   │ OR  │      Layer 2
   └─────┘   └─────┘
      │         │
      ▼         ▼
      Q        Qn
  • Q = AND(OR, NAND) = XOR
  • Qn = OR(NOR, AND) = XNOR
Parameters
Inputs 2
Outputs 2
Neurons 6
Layers 2
Parameters 18
Magnitude 19
Application: Binary Counter

T flip-flops with T=1 create divide-by-2 counters:

q = 0
for _ in range(8):
    q = t_flipflop(1, q)  # toggles: 0,1,0,1,0,1,0,1

Chain multiple T flip-flops for multi-bit counters.

Usage
from safetensors.torch import load_file

w = load_file('model.safetensors')

# Toggle mode creates oscillation
q = 0
for _ in range(4):
    q_next = compute(t=1, q_prev=q, w)
    q = q_next  # 0 -> 1 -> 0 -> 1
License

MIT

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

5
Total runs
0
24-hour runs
-3
3-day runs
-6
7-day runs
-2
30-day runs

More Information About threshold-t-flipflop huggingface.co Model

More threshold-t-flipflop license Visit here:

https://choosealicense.com/licenses/mit

threshold-t-flipflop huggingface.co

threshold-t-flipflop huggingface.co is an AI model on huggingface.co that provides threshold-t-flipflop's model effect (), which can be used instantly with this phanerozoic threshold-t-flipflop model. huggingface.co supports a free trial of the threshold-t-flipflop model, and also provides paid use of the threshold-t-flipflop. Support call threshold-t-flipflop model through api, including Node.js, Python, http.

threshold-t-flipflop huggingface.co Url

https://huggingface.co/phanerozoic/threshold-t-flipflop

phanerozoic threshold-t-flipflop online free

threshold-t-flipflop huggingface.co is an online trial and call api platform, which integrates threshold-t-flipflop's modeling effects, including api services, and provides a free online trial of threshold-t-flipflop, you can try threshold-t-flipflop online for free by clicking the link below.

phanerozoic threshold-t-flipflop online free url in huggingface.co:

https://huggingface.co/phanerozoic/threshold-t-flipflop

threshold-t-flipflop install

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

threshold-t-flipflop install url in huggingface.co:

https://huggingface.co/phanerozoic/threshold-t-flipflop

Url of threshold-t-flipflop

threshold-t-flipflop huggingface.co Url

Provider of threshold-t-flipflop huggingface.co

phanerozoic
ORGANIZATIONS

Other API from phanerozoic

huggingface.co

Total runs: 84
Run Growth: 48
Growth Rate: 57.14%
Updated:September 26 2026