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Model: reaperdoesntknow/Symbiotic-8B
Source: Original Platform

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README.md

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+---
+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*
+
+<!-- CIX-CROSSLINK-START -->
+
+---
+
+## 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*
+
+<!-- CIX-CROSSLINK-END -->
+<!-- cix-keeper-ts:2026-05-04T15:26:02Z -->

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+  "vocab_size": 151936
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+  "chat_template": "{%- if tools %}\n    {{- '<|im_start|>system\\n' }}\n    {%- if messages[0].role == 'system' %}\n        {{- messages[0].content + '\\n\\n' }}\n    {%- endif %}\n    {{- \"# Tools\\n\\nYou may call one or more functions to assist with the user query.\\n\\nYou are provided with function signatures within <tools></tools> XML tags:\\n<tools>\" }}\n    {%- for tool in tools %}\n        {{- \"\\n\" }}\n        {{- tool | tojson }}\n    {%- endfor %}\n    {{- \"\\n</tools>\\n\\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\\n<tool_call>\\n{\\\"name\\\": <function-name>, \\\"arguments\\\": <args-json-object>}\\n</tool_call><|im_end|>\\n\" }}\n{%- else %}\n    {%- if messages[0].role == 'system' %}\n        {{- '<|im_start|>system\\n' + messages[0].content + '<|im_end|>\\n' }}\n    {%- endif %}\n{%- endif %}\n{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}\n{%- for message in messages[::-1] %}\n    {%- set index = (messages|length - 1) - loop.index0 %}\n    {%- if ns.multi_step_tool and message.role == \"user\" and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}\n        {%- set ns.multi_step_tool = false %}\n        {%- set ns.last_query_index = index %}\n    {%- endif %}\n{%- endfor %}\n{%- for message in messages %}\n    {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) %}\n        {{- '<|im_start|>' + message.role + '\\n' + message.content + '<|im_end|>' + '\\n' }}\n    {%- elif message.role == \"assistant\" %}\n        {%- set content = message.content %}\n        {%- set reasoning_content = '' %}\n        {%- if message.reasoning_content is defined and message.reasoning_content is not none %}\n            {%- set reasoning_content = message.reasoning_content %}\n        {%- else %}\n            {%- if '</think>' in message.content %}\n                {%- set content = message.content.split('</think>')[-1].lstrip('\\n') %}\n                {%- set reasoning_content = message.content.split('</think>')[0].rstrip('\\n').split('<think>')[-1].lstrip('\\n') %}\n            {%- endif %}\n        {%- endif %}\n        {%- if loop.index0 > ns.last_query_index %}\n            {%- if loop.last or (not loop.last and reasoning_content) %}\n                {{- '<|im_start|>' + message.role + '\\n<think>\\n' + reasoning_content.strip('\\n') + '\\n</think>\\n\\n' + content.lstrip('\\n') }}\n            {%- else %}\n                {{- '<|im_start|>' + message.role + '\\n' + content }}\n            {%- endif %}\n        {%- else %}\n            {{- '<|im_start|>' + message.role + '\\n' + content }}\n        {%- endif %}\n        {%- if message.tool_calls %}\n            {%- for tool_call in message.tool_calls %}\n                {%- if (loop.first and content) or (not loop.first) %}\n                    {{- '\\n' }}\n                {%- endif %}\n                {%- if tool_call.function %}\n                    {%- set tool_call = tool_call.function %}\n                {%- endif %}\n                {{- '<tool_call>\\n{\"name\": \"' }}\n                {{- tool_call.name }}\n                {{- '\", \"arguments\": ' }}\n                {%- if tool_call.arguments is string %}\n                    {{- tool_call.arguments }}\n                {%- else %}\n                    {{- tool_call.arguments | tojson }}\n                {%- endif %}\n                {{- '}\\n</tool_call>' }}\n            {%- endfor %}\n        {%- endif %}\n        {{- '<|im_end|>\\n' }}\n    {%- elif message.role == \"tool\" %}\n        {%- if loop.first or (messages[loop.index0 - 1].role != \"tool\") %}\n            {{- '<|im_start|>user' }}\n        {%- endif %}\n        {{- '\\n<tool_response>\\n' }}\n        {{- message.content }}\n        {{- '\\n</tool_response>' }}\n        {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n            {{- '<|im_end|>\\n' }}\n        {%- endif %}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|im_start|>assistant\\n' }}\n    {%- if enable_thinking is defined and enable_thinking is false %}\n        {{- '<think>\\n\\n</think>\\n\\n' }}\n    {%- endif %}\n{%- endif %}",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "extra_special_tokens": {},
+  "model_max_length": 131072,
+  "pad_token": "<|endoftext|>",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null
+}