Create README.md

README.md

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+````yaml
+---
+license: apache-2.0
+language:
+  - en
+library_name: llama.cpp
+tags:
+  - gguf
+  - quantized
+  - int8
+  - offline-ai
+  - local-llm
+  - chatnonet
+model_type: causal
+inference: true
+pipeline_tag: text-generation
+---
+
+# Model Card for ChatNONET
+
+**ChatNONET** is a family of **offline**, quantized large language models fine-tuned for **question answering** with **direct, concise answers**. Designed for local execution using `llama.cpp`, ChatNONET is available in multiple sizes and optimized for Android or Python-based environments.
+
+## Model Details
+
+### Model Description
+
+ChatNONET is intended for lightweight offline use, particularly on local devices like mobile phones or single-board computers. The models have been **fine-tuned for direct-answer QA** and quantized to **int8 (q8_0)** using `llama.cpp`.
+
+| Model Name                        | Base Model         | Size   |
+|----------------------------------|--------------------|--------|
+| ChatNONET-135m-tuned-q8_0.gguf   | Smollm             | 135M   |
+| ChatNONET-300m-tuned-q8_0.gguf   | Smollm             | 300M   |
+| ChatNONET-1B-tuned-q8_0.gguf     | LLaMA 3.2          | 1B     |
+| ChatNONET-3B-tuned-q8_0.gguf     | LLaMA 3.2          | 3B     |
+
+- **Developed by:** McaTech (Michael Cobol Agan)
+- **Model type:** Causal decoder-only transformer
+- **Languages:** English
+- **License:** Apache 2.0
+- **Finetuned from:**
+  - Smollm (135M, 300M variants)
+  - LLaMA 3.2 (1B, 3B variants)
+
+## Uses
+
+### Direct Use
+
+- Offline QA chatbot
+- Local assistants (no internet required)
+- Embedded Android or Python apps
+
+### Downstream Use
+
+- Try the **Android app**: [Download ChatNONET APK](https://drive.google.com/file/d/1-5Ozx_VsOUBS5_b4yS40MCaNZge_5_1f/view?usp=sharing)
+
+### Out-of-Scope Use
+
+- Long-form text generation
+- Tasks requiring real-time web access
+- Creative storytelling or coding tasks
+
+## Bias, Risks, and Limitations
+
+ChatNONET may reproduce biases present in its base models or fine-tuning data. Outputs should not be relied upon for sensitive or critical decisions.
+
+### Recommendations
+
+- Validate important responses
+- Choose model size based on your device capability
+- Avoid over-reliance for personal or legal advice
+
+## How to Get Started with the Model
+
+```bash
+# Clone llama.cpp and build it
+git clone https://github.com/ggerganov/llama.cpp
+cd llama.cpp
+make
+
+# Run the model
+./llama-run -m ./ChatNONET-300m-tuned-q8_0.gguf -p "What is gravity?"
+````
+
+## Training Details
+
+* **Finetuning Goal:** Direct-answer question answering
+* **Precision:** FP16 mixed precision
+* **Frameworks:** PyTorch, Transformers, Bitsandbytes
+* **Quantization:** int8 GGUF (`q8_0`) via `llama.cpp`
+
+## Evaluation
+
+* Evaluated internally on short QA prompts
+* Capable of direct factual or logical answers
+* Larger models perform better on reasoning tasks
+
+## Technical Specifications
+
+* **Architecture:**
+
+  * Smollm (135M, 300M)
+  * LLaMA 3.2 (1B, 3B)
+* **Format:** GGUF
+* **Quantization:** q8\_0 (int8)
+* **Deployment:** Mobile (Android) and desktop via `llama.cpp`
+
+## Citation
+
+```bibtex
+@misc{chatnonet2025,
+  title={ChatNONET: Offline Quantized Q&A Models},
+  author={Michael Cobol Agan},
+  year={2025},
+  note={\url{https://huggingface.co/your-model-repo}},
+}
+```
+
+## Contact
+
+* **Author:** Michael Cobol Agan (McaTech)
+* **Website / Download App:** https://mcatech.odoo.com/innovation
+
+```