reaperdoesntknow/Symbiotic-1B
SymbioticLM-1B by reaperdoesntknow is a 1 billion parameter hybrid symbolic-transformer model, built on a Qwen-1B backbone. It integrates a rotary transformer with a symbolic processing pipeline and persistent episodic memory for enhanced reasoning. This model is optimized for lightweight, memory-augmented symbolic inference in constrained environments, excelling at tasks like procedural planning, math modeling, and graph-based explanation generation.
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Overview
SymbioticLM-1B is a compact, 1 billion parameter hybrid model developed by reaperdoesntknow, part of the Convergent Intelligence LLC: Research Division portfolio. It combines a Qwen-1B rotary transformer with a unique symbolic processing pipeline and a persistent episodic memory system. This architecture is designed for memory-augmented reasoning and is particularly suited for CPU and embedded inference environments.
Key Capabilities & Architecture Highlights
- Hybrid Architecture: Fuses a Qwen-1B transformer backbone with a symbolic processing engine.
- Symbolic Memory: Features 2048 symbolic vectors with entropic and contextual retrieval for enhanced reasoning.
- Cognitive Engine: Includes advanced symbolic modules like ThoughtDynamicsLNN, CrystallineProcessor (DNAConv GNN), LiquidThoughtProcessor, and HelicalDNAProcessor.
- Dream Mode: Supports symbolic simulation via a ThoughtGenerator.
- Discrepancy Calculus Foundation: Developed under the DISC framework, which treats training singularities as structural signals for learning geometry.
Intended Uses
- CPU-optimized symbolic inference.
- Educational agents requiring memory and reasoning.
- Graph-based explanation generation.
- Procedural planning, math modeling, and small-code generation.
Limitations
- Less fluent in free-form language compared to larger, purely generative models.
- Symbolic accuracy benefits from memory curation.
- Dream Mode may require warm-up or symbolic seeding for complex queries.