| | --- |
| | 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` |
| |
|
| |
|
| |
|
| |
|
| | --- |
| |
|
| | ## 📎 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." |
| | ```` |
| |
|
| | --- |
| |
|
| | ## 📁 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 |
| |
|
| | --- |
| |
|
| |
|
| |
|
