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threshold-pruner
phanerozoic/threshold-pruner
threshold-pruner 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.
Multi-method pruning framework for threshold logic circuits.
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Public
Updated Jan 24, 2026
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.py55 KB · 89%
At a glance
- Access
- Public
- Created
- Jan 22, 2026
- Updated
- Jan 24, 2026
- SHA
- 5a44526b
Model card
From the Hugging Face model README
Threshold Pruner
Multi-method pruning framework for threshold logic circuits.
Methods
| Method | Flag | Description |
|---|---|---|
| Magnitude Reduction | mag | Reduce weights by 1 toward zero |
| Batched Magnitude | batched | GPU-parallel magnitude reduction |
| Zero Pruning | zero | Set weights directly to 0 |
| Quantization | quant | Force weights to {-1, 0, 1} |
| Evolutionary | evo | Mutation + selection with parsimony |
| Simulated Annealing | anneal | Gradual cooling search |
| Pareto Search | pareto | Correctness vs size tradeoff |
Usage
# List available circuits
python prune.py --list
# Prune a circuit with all methods
python prune.py threshold-hamming74decoder
# Specific methods only
python prune.py threshold-hamming74decoder --methods mag,zero,evo
# Batch process
python prune.py --all --max-inputs 8
# Save best result
python prune.py threshold-hamming74decoder --save
Requirements
torch
safetensors
Circuit Format
Each circuit needs:
threshold-{name}/
├── model.safetensors # Weights: {layer.weight: [...], layer.bias: [...]}
├── model.py # Forward function
├── config.json # {inputs, outputs, neurons, layers, parameters}
Related
License
MIT
- Created
- Jan 22, 2026
- Updated
- Jan 24, 2026