Instructions to use Raiff1982/Codette2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Adapters
How to use Raiff1982/Codette2 with Adapters:
from adapters import AutoAdapterModel model = AutoAdapterModel.from_pretrained("undefined") model.load_adapter("Raiff1982/Codette2", set_active=True) - Notebooks
- Google Colab
- Kaggle
| license: mit | |
| tags: | |
| - cognitive-ai | |
| - neuro-symbolic | |
| - multimodal | |
| - ethics | |
| - quantum | |
| - gradio-app | |
| - codette2 | |
| model-index: | |
| - name: Codette2 | |
| results: [] | |
| language: | |
| - en | |
| datasets: | |
| - Raiff1982/Codettesspecial | |
| base_model: | |
| - Raiff1982/Codettev2 | |
| - Raiff1982/autotrain-156ul-mfqfp | |
| library_name: adapter-transformers | |
| # 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 | |
| Technical Specifications | |
| Architecture and Objective | |
| Codette2 extends GPT-4.1 with modular agents (ethics, emotion, quantum, creativity, symbolic logic). | |
| Citation | |
| BibTeX: | |
| Always show details | |
| @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 | |
| """ |