reaperdoesntknow/Symiotic-14B

TEXT GENERATIONConcurrent Unit Cost:1Model Size:14BQuant:FP8Context Size:32kTool Calling:SupportedPublished:May 6, 2025License:afl-3.0Architecture:Transformer0.0K Featherless Exclusive Cold

reaperdoesntknow/Symiotic-14B is a 17.8 billion parameter symbolic–transformer hybrid model built on Qwen-14B, developed by Convergent Intelligence LLC. It integrates neural representation with structured symbolic cognition, featuring persistent memory, entropic recall, and self-organizing knowledge structures. This model is designed for advanced reasoning agents, symbolic math, code generation, and multi-step conversational agents requiring true memory.

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SymbioticLM-14B: A Hybrid Symbolic-Transformer Model

SymbioticLM-14B, developed by Convergent Intelligence LLC, is a 17.8 billion parameter hybrid model that combines a Qwen-14B transformer backbone with advanced symbolic cognition modules. This unique architecture allows for tight coupling of high-capacity neural representation with structured symbolic processing, aiming to excel in symbolic domains.

Key Capabilities & Features

  • Hybrid Architecture: Integrates a Qwen-14B transformer with specialized symbolic modules like ThoughtDynamicsLNN, LiquidThoughtProcessor, and CrystallineProcessor.
  • Persistent Memory: Features 4096 symbolic states in FP32, retrieved using entropy and contextual similarity, enabling true memory for long-term interactions.
  • Symbolic Evolution: Supports generative symbolic evolution and self-organizing knowledge structures, underpinned by Discrepancy Calculus (DISC) for dynamic completeness and stability.
  • Dream Mode: Includes a background symbolic simulation for open-ended cognition.
  • Advanced Routing: Utilizes an intent classifier and entropy gating to select appropriate processor paths.

Ideal Use Cases

  • Advanced Reasoning Agents: For complex, multi-step problem-solving.
  • Symbolic Math & Code Generation: Excels in tasks requiring structured logical output.
  • Conversational Agents: Designed for interactions demanding true memory and long-form symbolic theorem generation.
  • Scientific Dialogue & Simulations: Suitable for reasoning in fuzzy or discontinuous problem domains.