---
license: apache-2.0
tags:
- convergentintel
- swarm-intelligence
---

# S-AGI

By Convergent Intelligence LLC: Research Division

---

## Convergent Intelligence Portfolio

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


### Related Models

| Model | Downloads | Format |
|-------|-----------|--------|
| [SMOLM2Prover](https://huggingface.co/reaperdoesntknow/SMOLM2Prover) | 56 | HF |
| [SMOLM2Prover-GGUF](https://huggingface.co/reaperdoesntknow/SMOLM2Prover-GGUF) | 150 | GGUF |
| [DeepReasoning_1R](https://huggingface.co/reaperdoesntknow/DeepReasoning_1R) | 16 | HF |
| [SAGI](https://huggingface.co/reaperdoesntknow/SAGI) | 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 12:58 UTC*

## 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)