Upload README_codette2_hf.md

README_codette2_hf.md

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+---
+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: [email protected]