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README.md

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+---
+license: mit
+tags:
+- pytorch
+- safetensors
+- threshold-logic
+- neuromorphic
+- conversion
+---
+
+# threshold-bcd2binary
+
+Single digit BCD to binary converter. For digits 0-9.
+
+## Parameters
+
+| | |
+|---|---|
+| Inputs | 4 |
+| Outputs | 4 |
+| Parameters | 20 |
+
+## License
+
+MIT

config.json

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+{
+  "name": "threshold-bcd2binary",
+  "description": "BCD to binary converter",
+  "inputs": 4,
+  "outputs": 4,
+  "neurons": 4,
+  "layers": 1,
+  "parameters": 20
+}

create_safetensors.py

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+import torch
+from safetensors.torch import save_file
+
+weights = {}
+
+# Single digit BCD (4 bits) to Binary (4 bits)
+# BCD: 0-9 encoded in 4 bits
+# Output: same value (identity for single digit)
+
+def add_neuron(name, w_list, bias):
+    weights[f'{name}.weight'] = torch.tensor([w_list], dtype=torch.float32)
+    weights[f'{name}.bias'] = torch.tensor([bias], dtype=torch.float32)
+
+# Pass through (BCD 0-9 is same as binary 0-9)
+for i in range(4):
+    w = [0.0] * 4
+    w[i] = 1.0
+    add_neuron(f'b{3-i}', w, -1.0)
+
+save_file(weights, 'model.safetensors')
+
+def bcd2binary(d3, d2, d1, d0):
+    return d3, d2, d1, d0
+
+print("Verifying BCD to Binary...")
+errors = 0
+for d in range(10):  # Valid BCD: 0-9
+    d3, d2, d1, d0 = (d>>3)&1, (d>>2)&1, (d>>1)&1, d&1
+    b3, b2, b1, b0 = bcd2binary(d3, d2, d1, d0)
+    result = b3*8 + b2*4 + b1*2 + b0
+    if result != d:
+        errors += 1
+
+if errors == 0:
+    print("All 10 test cases passed!")
+else:
+    print(f"FAILED: {errors} errors")
+
+mag = sum(t.abs().sum().item() for t in weights.values())
+print(f"Magnitude: {mag:.0f}")
+print(f"Parameters: {sum(t.numel() for t in weights.values())}")

model.safetensors

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+oid sha256:768272a75a13a3a15dd1bb88eba21094ce77155a0ef176d55bc81c078ab1a889
+size 592