reaperdoesntknow/Symbiotic-8B

SymbioticLM-8B

Model Type: Hybrid Symbolic–Transformer
Base Model: Qwen-8B
Framework: PyTorch + Transformers-compatible
Purpose: Long-memory symbolic reasoning + high-fidelity language generation

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Overview

SymbioticLM-8B is a state-of-the-art hybrid transformer model with built-in symbolic cognition. It combines an 8B Qwen-based transformer with modular symbolic processors and a persistent memory buffer. The model supports both general conversation and deep symbolic tasks such as theorem generation, logical chaining, and structured reasoning with retained memory across turns.

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Architecture Highlights

• Backbone: Qwen-8B rotary transformer
• Symbolic Dim: 4096
• Symbolic Modules:
  • ThoughtDynamicsLNN (multi-head LSTM attention)
  • CrystallineProcessor (DNAConv GNN)
  • LiquidThoughtProcessor (recurrent symbol folding)
  • HelicalDNAProcessor (helical linear projection)
• Memory: 2048 symbolic vectors (float32) with entropy-aware retrieval and contextual recall
• Dream Mode: Self-generates symbolic cognition offline

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Files Included

File	Description
model.bin	PyTorch weights (LFS tracked)
model.safetensors	Same weights in safetensors format (recommended)
memory.pt	Symbolic memory snapshot (entropic, pretrained)
config.json	Base model configuration
generation_config.json	Sampling and decoding config (temperature, top_p, etc.)
tokenizer.json	Tokenizer data with custom tags and structure
added_tokens.json	Extra tokens like <THM>, <PROOF>, <D_EPS>
special_tokens_map.json	Maps for special tokens used during generation

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Intended Uses

• General symbolic reasoning and logical conversation
• Memory-aware tutoring, research assistants
• Code + math proof modeling
• Context-persistent dialogue systems

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Limitations

• Not instruction-tuned (e.g., chat-style inputs may require prompt engineering)
• Larger memory buffer may increase CPU load slightly
• Symbolic inference is offline-evolved; memory must be actively seeded

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Citations

This model was designed and built from Discrepancy Analysis, paper to be published soon!