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autologic-slm-onnx – AI Model by stevenvo780 | AlphaNeural AI

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stevenvo780/
autologic-slm-onnx

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transformers.js

text-generation

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Autologic SLM - ONNX fp32

Fine-tuned Qwen2.5-0.5B model that translates natural language text into structured logic AST (JSON).

Model Details

Base model: Qwen/Qwen2.5-0.5B
Training: LoRA (r=16, alpha=32) on q/v/k/o_proj, bf16, 15 epochs
Dataset: 395 verified samples, 10 logic patterns (modus ponens, syllogisms, etc.)
Format: ONNX fp32 with KV cache (for Transformers.js)
Size: ~2.4 GB
RAM usage: ~2.2 GB at inference

Output Format

The model outputs JSON conforming to Autologic AST:

json

{
  "axioms": [
    {"name": "a1", "formulaJSON": {"type": "Connective", "operator": "IMPLIES",
      "left": {"type": "Atom", "id": "Llueve", "text": "llueve"},
      "right": {"type": "Atom", "id": "SueloMojado", "text": "suelo mojado"}}}
  ],
  "conclusions": [
    {"formulaJSON": {"type": "Atom", "id": "SueloMojado", "text": "suelo mojado"}}
  ]
}

Critical Notes

Must use fp32: int8/uint8 quantization destroys instruction following on 0.5B models
Must use exact training prompt format: ChatML with specific system prompt
Exported with task=text-generation-with-past (includes KV cache)
Tokenizer merges are strings (Transformers.js compatible)

Part of

Autologic - Automatic formalization of natural language to formal logic.