---
license: mit
tags:
  - cognitive-ai
  - neuro-symbolic
  - multimodal
  - ethics
  - quantum
  - gradio-app
  - codette2
model-index:
  - name: Codette2
    results: []
---

# Model Card for Codette2

Codette2 is a multi-agent cognitive assistant fine-tuned on GPT-4.1, integrating neuro-symbolic reasoning, ethical governance, quantum-inspired optimization, and multimodal analysis. It supports both creative generation and philosophical insight, with support for image/audio input and explainable decision logic.

## Model Details

### Model Description

- **Developed by:** Jonathan Harrison
- **Model type:** Cognitive Assistant (multi-agent)
- **Language(s):** English
- **License:** MIT
- **Fine-tuned from model:** GPT-4.1

### Model Sources

- **Repository:** https://www.kaggle.com/models/jonathanharrison1/codette2
- **Demo:** Gradio and Jupyter-ready

## Uses

### Direct Use

- Creative storytelling, ideation, poetry
- Ethical simulations and governance logic
- Image/audio interpretation
- AI research companion or philosophical simulator

### Out-of-Scope Use

- Clinical therapy or legal advice
- Deployment without ethical guardrails
- Bias-sensitive environments without further fine-tuning

## Bias, Risks, and Limitations

This model embeds filters to detect sentiment and flag unethical prompts, but no AI system is perfect. Outputs should be reviewed when used in sensitive contexts.

### Recommendations

Use with ethical filters enabled and log sensitive prompts. Augment with human feedback in mission-critical deployments.

## How to Get Started with the Model

```python
from ai_driven_creativity import AIDrivenCreativity
creator = AIDrivenCreativity()
print(creator.write_literature("Dreams of quantum AI"))
```

## Training Details

### Training Data

Custom dataset of ethical dilemmas, creative writing prompts, philosophical queries, and multimodal reasoning tasks.

### Training Hyperparameters

- **Epochs:** Variable (~450 steps)
- **Precision:** fp16
- **Loss achieved:** 0.00001

## Evaluation

### Testing Data

Ethical prompt simulations, sentiment evaluation, creative generation scores.

### Metrics

Manual eval + alignment tests on ethical response integrity, coherence, originality, and internal consistency.

### Results

Codette2 achieved stable alignment and response consistency across >450 training steps with minimal loss oscillation.

## Environmental Impact

- **Hardware Type:** NVIDIA A100 (assumed)
- **Hours used:** ~3.5
- **Cloud Provider:** Kaggle / Colab (assumed)
- **Carbon Emitted:** Estimated via [MLCO2](https://mlco2.github.io/impact)

## Technical Specifications

### Architecture and Objective

Codette2 extends GPT-4.1 with modular agents (ethics, emotion, quantum, creativity, symbolic logic).

## Citation

**BibTeX:**
```
@misc{codette2,
  author = {Jonathan Harrison},
  title = {Codette2: Cognitive Multi-Agent AI Assistant},
  year = 2025,
  howpublished = {Kaggle and HuggingFace}
}
```

**APA:**
Jonathan Harrison. (2025). *Codette2: Cognitive Multi-Agent AI Assistant*. Retrieved from HuggingFace.

## Contact

For issues, contact: jonathanharrison1@protonmail.com