Update README.md

README.md

@@ -8,38 +8,81 @@ tags:
 - merge
 
 ---
-# merged-medical-reasoning
 
-This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
 
-## Merge Details
-### Merge Method
+# 🧠 AgenticCoder‑4B
+
+**AgenticCoder‑4B** is a compact 4B parameter language model designed for autonomous agent workflows and intelligent code reasoning. It merges the planning and tool-use strengths of `Jan-nano` with the coding and logic capabilities of `Qwen3‑4B‑Code‑Reasoning`, creating a balanced model ideal for real-world assistant scenarios, research agents, and smart development tools.
+
+---
+
+## ✨ Key Features
+
+- 🔁 **Agentic Planning & MCP Alignment**  
+  Trained on datasets and architectures optimized for multi-step reasoning, task decomposition, and memory–contextual workflows.
+
+- 💻 **Code Understanding & Reasoning**  
+  Strong capabilities in Python code generation, script explanation, optimization, and multi-turn task development.
+
+- 🧰 **Tool Use Simulation**  
+  Handles realistic tool interaction prompts such as CSV analysis, OCR, and file parsing in code.
+
+- 📦 **Compact & Efficient (4B)**  
+  Lightweight enough for cost-efficient deployment, edge device integration, and fine-tuning.
+
+---
+
+## 🛠️ Merge Details
+
+- **Merge Method:** SLERP (`t = 0.4`)
+- **Base Model:** [`Menlo/Jan-nano`](https://huggingface.co/Menlo/Jan-nano)
+- **Merged With:** [`ertghiu256/qwen3-4b-code-reasoning`](https://huggingface.co/ertghiu256/qwen3-4b-code-reasoning)
+- **Precision:** `float16`
+- **Tokenizer Source:** `Menlo/Jan-nano`
+
 
-This model was merged using the [SLERP](https://en.wikipedia.org/wiki/Slerp) merge method.
 
-### Models Merged
 
-The following models were included in the merge:
-* [ertghiu256/qwen3-4b-code-reasoning](https://huggingface.co/ertghiu256/qwen3-4b-code-reasoning)
-* [Menlo/Jan-nano](https://huggingface.co/Menlo/Jan-nano)
+---
+
+## 📎 Example Use Cases
 
-### Configuration
+```text
+✅ "Design a 3-week beginner Python curriculum including AI tools."
+✅ "Write a Python function to recursively scan JSON for a key, without using recursion."
+✅ "Read a folder of images and extract text using OCR, save to files."
+✅ "Summarize trends in a sales CSV and visualize monthly performance."
+````
 
-The following YAML configuration was used to produce this model:
+---
 
-```yaml
+## 📁 License & Use
 
-merge_method: slerp
-base_model: Menlo/Jan-nano
+This model is provided for research and development use under the terms of the base models’ respective licenses. Please ensure compliance before commercial usage.
 
-models:
-  - model: Menlo/Jan-nano
-  - model: ertghiu256/qwen3-4b-code-reasoning
+---
 
-parameters:
-  t: 0.4   # 70% base (MedScholar), 30% Nemotron reasoning
+## 🧬 Citation
 
-dtype: float16
-tokenizer_source: Menlo/Jan-nano
+If you use this model, consider citing it as:
 
 ```
+@misc{agenticcoder4b2025,
+  title={AgenticCoder-4B: A Compact Agent + Code Reasoning Model},
+  author={Yasser, M.},
+  year={2025},
+  url={https://huggingface.co/your-username/AgenticCoder-4B}
+}
+```
+
+---
+
+## 🤝 Acknowledgements
+
+* [Menlo/Jan-nano](https://huggingface.co/Menlo/Jan-nano) by Menlo Systems
+* [Qwen3‑4B‑Code‑Reasoning](https://huggingface.co/ertghiu256/qwen3-4b-code-reasoning) by ertghiu256
+* MergeKit, SLERP, Hugging Face
+
+---
+
+