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README.md

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+---
+license: mit
+tags:
+- pytorch
+- safetensors
+- threshold-logic
+- neuromorphic
+---
+
+# threshold-binary2bcd
+
+binary2bcd threshold logic implementation.
+
+## License
+
+MIT

config.json

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+{
+  "name": "threshold-binary2bcd",
+  "description": "binary2bcd circuit",
+  "inputs": 8,
+  "outputs": 8,
+  "neurons": 8,
+  "layers": 2,
+  "parameters": 64
+}

create_safetensors.py

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+import torch
+from safetensors.torch import save_file
+
+weights = {}
+
+# 4-bit Binary to BCD (for 0-9, identity; 10-15 invalid)
+# Extended: detect if value >= 10 for two-digit output
+
+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 bits
+for i in range(4):
+    w = [0.0] * 4
+    w[i] = 1.0
+    add_neuron(f'd{3-i}', w, -1.0)
+
+# Detect >= 10 (for overflow into tens digit)
+add_neuron('ge10', [8.0, 4.0, 2.0, 1.0], -10.0)
+
+save_file(weights, 'model.safetensors')
+
+def binary2bcd(b3, b2, b1, b0):
+    val = b3*8 + b2*4 + b1*2 + b0
+    if val < 10:
+        return 0, b3, b2, b1, b0
+    else:
+        ones = val - 10
+        return 1, (ones>>3)&1, (ones>>2)&1, (ones>>1)&1, ones&1
+
+print("Verifying Binary to BCD...")
+errors = 0
+for b in range(16):
+    b3, b2, b1, b0 = (b>>3)&1, (b>>2)&1, (b>>1)&1, b&1
+    tens, d3, d2, d1, d0 = binary2bcd(b3, b2, b1, b0)
+    result = tens * 10 + d3*8 + d2*4 + d1*2 + d0
+    if result != b:
+        errors += 1
+
+if errors == 0:
+    print("All 16 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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+version https://git-lfs.github.com/spec/v1
+oid sha256:7b32cedd67f13aef13801b6e1f5b0da6bef160244949e56420fcb4c02fa81fcc
+size 748