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

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.

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

Files Included

Intended Uses

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

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

Citations

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