---
base_model:
- ertghiu256/qwen3-4b-code-reasoning
- Menlo/Jan-nano
library_name: transformers
tags:
- mergekit
- merge

---


# 🧠 AgenticCoder‑4B

<img src="banner.png" width="800" />

**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`




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## 📎 Example Use Cases

```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."
````

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## 📁 License & Use

This model is provided for research and development use under the terms of the base models’ respective licenses. Please ensure compliance before commercial usage.

---

## 🧬 Citation

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

---