---
base_model:
- Tesslate/UIGEN-X-4B-0729
- Menlo/Jan-nano
library_name: transformers
tags:
- mergekit
- merge

---

## 🧠 AgentUX‑4B

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

**AgentUX‑4B** is a compact, agentic reasoning model designed for **UI layout generation**, **component reasoning**, and **lightweight code structuring tasks**.
It’s a 4B-parameter model merged using **SLERP** (Spherical Linear Interpolation) via **MergeKit**, combining:

* 🔷 **60%** [`Tesslate/UIGEN-X-4B-0729`](https://huggingface.co/Tesslate/UIGEN-X-4B-0729) — excellent at UI understanding and structured generation
* 🔹 **40%** [`Menlo/Jan-nano`](https://huggingface.co/Menlo/Jan-nano) — strong generalist with compact tool-use and agentic reasoning

---

### ✨ Highlights

* 📐 **UI reasoning & layout structure understanding**
* 🧩 **Component-to-code generation (HTML, JSX, CSS fragments)**
* 🧠 **Compact agentic planning and multi-step reasoning**
* ⚡ **Lightweight & merge-optimized** for local inference and real-time apps
* 🧬 **Merged using SLERP** to preserve semantic smoothness between sources

---

### 🧪 Example Use Cases

| Prompt                                             | Task                       |
| -------------------------------------------------- | -------------------------- |
| "Generate a signup form layout using HTML and CSS" | Frontend layout generation |
| "Explain the role of `flex-wrap` in UI design"     | UI reasoning               |
| "Plan 3 steps to build a sidebar menu using React" | Agentic decomposition      |

---

### 🔧 Usage Example

```python
from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)
```

---

### 🛠 Merge Details

* 🔗 MergeKit method: `slerp`
* 🔍 Focused on reasoning alignment between structured generation (UIGEN) and agent-style planning (Jan-nano)
* 🤖 No additional fine-tuning post-merge

---

### 📘 License & Credit

* Model licensed under Apache 2.0
* All credit to the original base models:

  * [`Tesslate/UIGEN-X-4B-0729`](https://huggingface.co/Tesslate/UIGEN-X-4B-0729)
  * [`Menlo/Jan-nano`](https://huggingface.co/Menlo/Jan-nano)

---