---
license: cc-by-nc-nd-4.0
tags:
- waveformer
- Kuramoto
- phase-synchronization
- continuous-time
- attention-free
- oscillator
- system-omega
- event-prediction
- proprietary-implementation
language:
- en
pipeline_tag: text-generation
---

# Waveformer / System Omega

This repository is the public Hugging Face surface for Nossair Bajddi's Waveformer/System Omega research line.

Current evidence-map technical note: https://doi.org/10.5281/zenodo.21044769

It is intentionally not a public trained-weights release. The core trained implementation, model weights, checkpoints, CUDA kernels, datasets, tokenizer files, and training recipes remain proprietary and are not released here.

## Repository contents

This repository contains a public Hugging Face compatibility / architecture surface for the Waveformer line:

- `README.md` - public evidence map and validation-status summary
- `config.json` - public Waveformer configuration metadata
- `configuration_waveformer.py` - public custom Transformers config class
- `modeling_waveformer.py` - public architecture-surface wrapper

This repository does not contain:

- trained weights
- tokenizer files
- checkpoints
- CUDA kernels
- datasets
- exact data curation recipes
- training recipes
- the proprietary trained Waveformer/System Omega engine

Because trained weights are not included, this repository should not be read as a normal downloadable model checkpoint. It is a public proof/provenance and architecture landing surface for the Waveformer/System Omega research line.

## Public evidence chain

| Date | Record | DOI | Role |
|---|---|---|---|
| 2026-05-27 | Continuous Oscillator Intelligence Runtime - Timestamp Proof | https://doi.org/10.5281/zenodo.20412409 | Timestamp and priority proof using SHA256 hashes of source/checkpoint artifacts. |
| 2026-06-16 | Deterministic Layer Freezing via Continuous Phase Coherence Analysis | https://doi.org/10.5281/zenodo.20720827 | Phase-coherence layer analysis across GPT-2, Qwen2.5, and Mistral scales. |
| 2026-06-18 | Emergence Over Attention: Continuous-Time Phase Synchronization as a Computational Primitive | https://doi.org/10.5281/zenodo.20741536 | Waveformer architecture and training report. |
| 2026-06-23 | Non-Autoregressive Semantic Steering of Discrete Language Models via Continuous-Time Phase Manifolds | https://doi.org/10.5281/zenodo.20819119 | System Omega semantic-steering report and raw validation metrics. |
| 2026-06-29 | Waveformer / System Omega: Public Evidence Map and Current Validation Status | https://doi.org/10.5281/zenodo.21044769 | Consolidates the public DOI trail, private IP boundary, current validation status, and explicit non-claims. |

## How to read this repository

The public records above are different proof classes:

- The May 27 record is a timestamp/provenance anchor.
- The June 16 record is a phase-coherence method and empirical report.
- The June 18 record is the Waveformer architecture and training report.
- The June 23 record is the System Omega semantic-steering report.
- The June 29 record is a consolidation/status technical note that maps the public proof trail, private IP boundary, current validation status, and explicit non-claims.
- This Hugging Face repository is the AI-community landing surface tying those records together.

Public reproducibility would require releasing trained weights, source code, kernels, checkpoints, datasets, and recipes. That is intentionally outside the current public release boundary.

## Current validation status

The current strongest result is not chatbot replacement or product-grade token generation. It is runtime-state event forecasting.

Private audit summary, 2026-06-29:

- System Omega runtime state predicts future internal error spikes on real telemetry with AUC around 0.95 to 0.99 across tested horizons.
- Fixed-state online operation was verified over a 1,048,576-token stream with flat allocated tensor memory.
- The load-bearing mechanism is saved phase/velocity plus bidirectional cross-coupling; ablation destroys the low-mode fossil when velocity or cross-coupling is removed.
- Predictive-maintenance/degradation streams are the strongest external use-path, especially when Omega/Waveformer state is combined with native features.

## Current non-claims

This repository does not claim that:

- Waveformer currently beats frontier LLMs.
- The current public repository is a runnable trained model release.
- The current token-generation UX is product-grade.
- Markets, earthquakes, or Wikipedia attention streams are standalone product-grade wins.
- Current Fractal/Phi-4 LoRA bridge artifacts are crystallized.
- Public reproducibility is provided.

This repository also does not release proprietary source code, trained weights, checkpoints, CUDA kernels, datasets, tokenizer files, or training recipes.

## Usage

This is not a public trained-weights release.

Do not expect the following to load a trained Waveformer checkpoint from this repository:

```python
from transformers import AutoModelForCausalLM

model = AutoModelForCausalLM.from_pretrained(
    "wannaq/Waveformer",
    trust_remote_code=True,
)
```

The trained weights are intentionally not included. The repository is maintained as a public proof/provenance and architecture surface. See the Zenodo DOI chain above for the formal public records.

## Research direction

Based on the strongest surviving evidence, the most credible current direction is stateful event forecasting and monitoring: detecting future instability, degradation, failure, or regime change in continuous streams.

Relevant private application areas include:

- local AI telemetry monitoring
- experiment-governor systems
- predictive maintenance and degradation monitoring
- GPU/training health monitoring
- autonomous verification pipelines
- closed-source research engineering
- private continuous-state event-prediction systems


## Citation anchors

```bibtex
@misc{bajddi2026runtime,
  author = {Bajddi, Nossair},
  title = {Continuous Oscillator Intelligence Runtime - Timestamp Proof},
  year = {2026},
  publisher = {Zenodo},
  doi = {10.5281/zenodo.20412409},
  url = {https://doi.org/10.5281/zenodo.20412409}
}

@misc{bajddi2026phasecoherence,
  author = {Bajddi, Nossair},
  title = {Deterministic Layer Freezing in Autoregressive Language Models via Continuous Phase Coherence Analysis},
  year = {2026},
  publisher = {Zenodo},
  doi = {10.5281/zenodo.20720827},
  url = {https://doi.org/10.5281/zenodo.20720827}
}

@misc{bajddi2026waveformer,
  author = {Bajddi, Nossair},
  title = {Emergence Over Attention: Continuous-Time Phase Synchronization as a Computational Primitive},
  year = {2026},
  publisher = {Zenodo},
  doi = {10.5281/zenodo.20741536},
  url = {https://doi.org/10.5281/zenodo.20741536}
}

@misc{bajddi2026omega,
  author = {Bajddi, Nossair},
  title = {Non-Autoregressive Semantic Steering of Discrete Language Models via Continuous-Time Phase Manifolds},
  year = {2026},
  publisher = {Zenodo},
  doi = {10.5281/zenodo.20819119},
  url = {https://doi.org/10.5281/zenodo.20819119}
}

@misc{bajddi2026evidencemap,
  author = {Bajddi, Nossair},
  title = {Waveformer / System Omega: Public Evidence Map and Current Validation Status},
  year = {2026},
  publisher = {Zenodo},
  doi = {10.5281/zenodo.21044769},
  url = {https://doi.org/10.5281/zenodo.21044769}
}
```