reaperdoesntknow/Symiotic-14B
TEXT GENERATIONConcurrency Cost:1Model Size:14BQuant:FP8Ctx Length:32kTool Calling:SupportedPublished:May 6, 2025License:afl-3.0Architecture:Transformer0.0K Cold
SymbioticLM-14B by reaperdoesntknow is a 17.8 billion parameter hybrid symbolic–transformer model built on Qwen-14B. It integrates neural representation with structured symbolic cognition, featuring persistent memory, multi-stage symbolic routing, and self-organizing knowledge structures. This model is optimized for advanced cognitive reasoning, symbolic math, code generation, and scientific dialogue in complex problem domains.
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SymbioticLM-14B: Hybrid Symbolic–Transformer Model
SymbioticLM-14B is a 17.8 billion parameter model developed by reaperdoesntknow, combining a Qwen-14B transformer backbone with advanced symbolic processing. This hybrid architecture aims to surpass traditional LLMs in symbolic domains by tightly coupling neural and symbolic cognition.
Key Capabilities
- Hybrid Architecture: Integrates a Qwen-14B transformer with specialized symbolic modules like ThoughtDynamicsLNN, LiquidThoughtProcessor, CrystallineProcessor (DNAConv GNN), and HelicalDNAProcessor.
- Persistent Memory: Features 4096 symbolic states in FP32, retrieved using entropy and contextual similarity, enabling true memory for multi-step interactions.
- Advanced Reasoning: Supports multi-stage symbolic routing and self-organizing knowledge structures, grounded in Discrepancy Calculus for dynamic completeness and stability.
- Dream Mode: Includes a background symbolic simulation for open-ended cognitive processes.
- Symbolic Tag Support: Utilizes a custom tokenizer with added tokens for symbolic tags like
<D_LIM>and<PROOF>.
Good For
- Advanced Reasoning Agents: Ideal for complex cognitive tasks requiring deep understanding and structured thought.
- Symbolic Math & Code Generation: Excels in long-form symbolic theorem generation, proof planning, and synthesizing mathematical or programming constructs.
- Scientific Dialogue & Simulation: Suitable for scientific discourse and symbolic simulations in fuzzy or discontinuous problem domains.
- Conversational Agents with Memory: Designed for multi-step conversations that require true, persistent memory and entropic recall.