---
license: afl-3.0
datasets:
- 0xZee/dataset-CoT-Advanced-Calculus-268
language:
- en
base_model:
- Qwen/Qwen3-8B
pipeline_tag: text-generation
library_name: transformers
tags:
- qwen3
- 8b
- qwen3-8b
- symbiotic
- symbtioicai
- convergentintel
---

# 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

| 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        |

---

## 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

---

## Discrepancy Calculus Foundation

This model is part of the [Convergent Intelligence LLC: Research Division](https://huggingface.co/reaperdoesntknow) portfolio. All models in this portfolio are developed under the Discrepancy Calculus (DISC) framework — a measure-theoretic approach to understanding and controlling the gap between what a model *should* produce and what it *actually* produces.

DISC treats training singularities (loss plateaus, mode collapse, catastrophic forgetting) not as failures to be smoothed over, but as **structural signals** that reveal the geometry of the learning problem. Key concepts:

- **Discrepancy Operator (D):** Measures the gap between expected and observed behavior at each training step
- **Jump Sets:** Boundaries where model behavior changes discontinuously — these are *features*, not bugs
- **Ghost Imprinting:** Teacher knowledge that transfers to student models through weight-space topology rather than explicit distillation signal

For the full mathematical treatment, see [Discrepancy Calculus: Foundations and Core Theory](https://huggingface.co/reaperdoesntknow/Discrepancy_Calculus) (DOI: 10.57967/hf/8194).

**Citation chain:** [Structure Over Scale](https://huggingface.co/reaperdoesntknow/Structure-Over-Scale) (DOI: 10.57967/hf/8165) → [Three Teachers to Dual Cognition](https://huggingface.co/reaperdoesntknow/DualMind_Methodolgy) (DOI: 10.57967/hf/8184) → [Discrepancy Calculus](https://huggingface.co/reaperdoesntknow/Discrepancy_Calculus) (DOI: 10.57967/hf/8194)

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

---

## Convergent Intelligence Portfolio

*Part of the [Symbiotic AI Series](https://huggingface.co/reaperdoesntknow) by [Convergent Intelligence LLC: Research Division](https://huggingface.co/reaperdoesntknow)*


### Related Models

| Model | Downloads | Format |
|-------|-----------|--------|
| [Symbiotic-1B](https://huggingface.co/reaperdoesntknow/Symbiotic-1B) | 4 | HF |
| [Symiotic-14B](https://huggingface.co/reaperdoesntknow/Symiotic-14B) | 3 | HF |
| [Symbiotic-Beta](https://huggingface.co/reaperdoesntknow/Symbiotic-Beta) | 3 | HF |

### Top Models from Our Lab

| Model | Downloads |
|-------|-----------|
| [Qwen3-1.7B-Thinking-Distil](https://huggingface.co/reaperdoesntknow/Qwen3-1.7B-Thinking-Distil) | 501 |
| [LFM2.5-1.2B-Distilled-SFT](https://huggingface.co/reaperdoesntknow/LFM2.5-1.2B-Distilled-SFT) | 342 |
| [Qwen3-1.7B-Coder-Distilled-SFT](https://huggingface.co/reaperdoesntknow/Qwen3-1.7B-Coder-Distilled-SFT) | 302 |
| [Qwen3-0.6B-Distilled-30B-A3B-Thinking-SFT-GGUF](https://huggingface.co/reaperdoesntknow/Qwen3-0.6B-Distilled-30B-A3B-Thinking-SFT-GGUF) | 203 |
| [Qwen3-1.7B-Coder-Distilled-SFT-GGUF](https://huggingface.co/reaperdoesntknow/Qwen3-1.7B-Coder-Distilled-SFT-GGUF) | 194 |

**Total Portfolio: 41 models | 2,781 total downloads**


*Last updated: 2026-03-28 12:57 UTC*

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---

## From the Convergent Intelligence Portfolio

**[DistilQwen Collection](https://huggingface.co/collections/reaperdoesntknow/distilqwen-69bf40ec669117e3f069ef1c)** — Our only BF16 series. Proof-weighted distillation from Qwen3-30B-A3B → 1.7B and 0.6B on H100. Three teacher variants (Instruct, Thinking, Coder), nine models, 2,788 combined downloads. The rest of the portfolio proves structure beats scale on CPU. This collection shows what happens when you give the methodology real hardware.

Top model: [Qwen3-1.7B-Coder-Distilled-SFT](https://huggingface.co/reaperdoesntknow/Qwen3-1.7B-Coder-Distilled-SFT) — 508 downloads

Full methodology: [Structure Over Scale (DOI: 10.57967/hf/8165)](https://doi.org/10.57967/hf/8165)

*Convergent Intelligence LLC: Research Division*

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