Instructions to use Apel-sin/UIGEN-T1.1-Qwen-14B-exl2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Apel-sin/UIGEN-T1.1-Qwen-14B-exl2 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Apel-sin/UIGEN-T1.1-Qwen-14B-exl2", dtype="auto") - Notebooks
- Google Colab
- Kaggle
add measurement.json
Browse files- README.md +193 -0
- measurement.json +0 -0
README.md
ADDED
|
@@ -0,0 +1,193 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
license: apache-2.0
|
| 3 |
+
datasets:
|
| 4 |
+
- smirki/UI_REASONING_v1.01
|
| 5 |
+
language:
|
| 6 |
+
- en
|
| 7 |
+
base_model:
|
| 8 |
+
- smirki/UIGEN-T1.1-Qwen-14B
|
| 9 |
+
tags:
|
| 10 |
+
- code
|
| 11 |
+
- ui
|
| 12 |
+
- generation
|
| 13 |
+
- uigen
|
| 14 |
+
library_name: transformers
|
| 15 |
+
---
|
| 16 |
+
|
| 17 |
+

|
| 18 |
+
|
| 19 |
+
# **Model Card for UIGEN-T1.1**
|
| 20 |
+
|
| 21 |
+
New and Improved reasoning traces. Better ui generation. Smarter decisions. Better code generation! Trained on a 700+ dataset.
|
| 22 |
+
USE BUDGET FORCING (putting the word answer or think at the end of the assistant generation to keep generationg more thinking and use 'answer' to write code.)
|
| 23 |
+
SFT on a 4090 for 4 hours.
|
| 24 |
+
|
| 25 |
+
## **Model Summary**
|
| 26 |
+
UIGEN-T1.1 is a **14-billion parameter transformer model** fine-tuned on **Qwen2.5-Coder-14B-Instruct**. It is designed for **reasoning-based UI generation**, leveraging a complex chain-of-thought approach to produce **robust HTML and CSS-based UI components**. Currently, it is limited to **basic applications such as dashboards, landing pages, and sign-up forms**.
|
| 27 |
+
|
| 28 |
+
## **Model Details**
|
| 29 |
+
|
| 30 |
+
### **Model Description**
|
| 31 |
+
UIGEN-T1.1 generates **HTML and CSS-based UI layouts** by reasoning through design principles. While it has a strong **chain-of-thought reasoning process**, it is currently **limited to text-based UI elements and simpler frontend applications**. The model **excels at dashboards, landing pages, and sign-up forms**, but **lacks advanced interactivity** (e.g., JavaScript-heavy functionalities).
|
| 32 |
+
|
| 33 |
+
- **Developed by:** [smirki](https://huggingface.co/smirki)
|
| 34 |
+
- **Shared by:** [smirki](https://huggingface.co/smirki)
|
| 35 |
+
- **Model type:** Transformer-based
|
| 36 |
+
- **Language(s) (NLP):** English
|
| 37 |
+
- **License:** Apache 2.0
|
| 38 |
+
- **Finetuned from model:** Qwen2.5-Coder-14B-Instruct
|
| 39 |
+
|
| 40 |
+
### **Model Sources**
|
| 41 |
+
- **Repository:** (Will be uploaded to GitHub soon)
|
| 42 |
+
- **Hosted on:** [Hugging Face](https://huggingface.co/smirki)
|
| 43 |
+
- **Demo:** Coming soon
|
| 44 |
+
|
| 45 |
+

|
| 46 |
+
|
| 47 |
+
|
| 48 |
+
## **Uses**
|
| 49 |
+
|
| 50 |
+
### **Direct Use**
|
| 51 |
+
- Generates HTML and CSS code for **basic UI elements**
|
| 52 |
+
- Best suited for **dashboards, landing pages, and sign-up forms**
|
| 53 |
+
- Requires **manual post-processing** to refine UI outputs
|
| 54 |
+
- **May require using the word "answer" at the end of the input prompt** to get better inference
|
| 55 |
+
|
| 56 |
+
### **Downstream Use (optional)**
|
| 57 |
+
- Can be fine-tuned further for **specific frontend frameworks (React, Vue, etc.)**
|
| 58 |
+
- May be integrated into **no-code/low-code UI generation tools**
|
| 59 |
+
|
| 60 |
+
### **Out-of-Scope Use**
|
| 61 |
+
- Not suitable for **complex frontend applications** involving JavaScript-heavy interactions
|
| 62 |
+
- May not generate **fully production-ready** UI code
|
| 63 |
+
- **Limited design variety** – biased towards **basic frontend layouts**
|
| 64 |
+
|
| 65 |
+
## **Bias, Risks, and Limitations**
|
| 66 |
+
|
| 67 |
+
### **Biases**
|
| 68 |
+
- **Strong bias towards basic frontend design patterns** (may not generate creative or advanced UI layouts)
|
| 69 |
+
- **May produce repetitive designs** due to limited training scope
|
| 70 |
+
|
| 71 |
+
### **Limitations**
|
| 72 |
+
- **Artifacting issues**: Some outputs may contain formatting artifacts
|
| 73 |
+
- **Limited generalization**: Performs best in **HTML + CSS UI generation**, but **not robust for complex app logic**
|
| 74 |
+
- **May require prompt engineering** (e.g., adding "answer" to input for better results)
|
| 75 |
+
|
| 76 |
+
## **How to Get Started with the Model**
|
| 77 |
+
|
| 78 |
+
### **Example Model Template**
|
| 79 |
+
```plaintext
|
| 80 |
+
<|im_start|>user
|
| 81 |
+
{question}<|im_end|>
|
| 82 |
+
<|im_start|>assistant
|
| 83 |
+
<|im_start|>think
|
| 84 |
+
{reasoning}<|im_end|>
|
| 85 |
+
<|im_start|>answer
|
| 86 |
+
```
|
| 87 |
+
|
| 88 |
+
### **Basic Inference Code**
|
| 89 |
+
```python
|
| 90 |
+
from transformers import AutoModelForCausalLM, AutoTokenizer
|
| 91 |
+
|
| 92 |
+
model_name = "smirki/UIGEN-T1.1-14B"
|
| 93 |
+
tokenizer = AutoTokenizer.from_pretrained(model_name)
|
| 94 |
+
model = AutoModelForCausalLM.from_pretrained(model_name).to("cuda")
|
| 95 |
+
|
| 96 |
+
prompt = """<|im_start|>user
|
| 97 |
+
Make a dark-themed dashboard for an oil rig.<|im_end|>
|
| 98 |
+
<|im_start|>assistant
|
| 99 |
+
<|im_start|>think
|
| 100 |
+
"""
|
| 101 |
+
|
| 102 |
+
inputs = tokenizer(prompt, return_tensors="pt").to("cuda")
|
| 103 |
+
outputs = model.generate(**inputs, max_new_tokens=12012, do_sample=True, temperature=0.7) #max tokens has to be greater than 12k
|
| 104 |
+
|
| 105 |
+
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
|
| 106 |
+
```
|
| 107 |
+
|
| 108 |
+
## **Training Details**
|
| 109 |
+
|
| 110 |
+
### **Training Data**
|
| 111 |
+
- **Based on:** Qwen2.5-Coder-14B-Instruct
|
| 112 |
+
- **Fine-tuned on:** UI-related datasets with reasoning-based HTML/CSS examples
|
| 113 |
+
|
| 114 |
+
### **Training Procedure**
|
| 115 |
+
- **Preprocessing:** Standard text-tokenization using Hugging Face transformers
|
| 116 |
+
- **Training Precision:** **bf16 mixed precision** quantized to q8
|
| 117 |
+
|
| 118 |
+
## **Evaluation**
|
| 119 |
+
|
| 120 |
+
### **Testing Data, Factors & Metrics**
|
| 121 |
+
- **Testing Data:** Internal UI design-related datasets
|
| 122 |
+
- **Evaluation Factors:** Bias towards basic UI components, robustness in reasoning, output quality
|
| 123 |
+
- **Metrics:** Subjective evaluation based on UI structure, correctness, and usability
|
| 124 |
+
|
| 125 |
+
### **Results**
|
| 126 |
+
- **Strengths:**
|
| 127 |
+
- **Good at reasoning-based UI layouts**
|
| 128 |
+
- **Generates structured and valid HTML/CSS**
|
| 129 |
+
- **Weaknesses:**
|
| 130 |
+
- **Limited design diversity**
|
| 131 |
+
- **Artifacting in outputs**
|
| 132 |
+
|
| 133 |
+
## **Technical Specifications**
|
| 134 |
+
|
| 135 |
+
### **Model Architecture and Objective**
|
| 136 |
+
- **Architecture:** Transformer-based LLM fine-tuned for UI reasoning
|
| 137 |
+
- **Objective:** Generate **robust frontend UI layouts with chain-of-thought reasoning**
|
| 138 |
+
|
| 139 |
+
### **Compute Infrastructure**
|
| 140 |
+
- **Hardware Requirements:** 12GB VRAM reccomended
|
| 141 |
+
- **Software Requirements:**
|
| 142 |
+
- Transformers library (Hugging Face)
|
| 143 |
+
- PyTorch
|
| 144 |
+
|
| 145 |
+
## **Citation**
|
| 146 |
+
If using this model, please cite:
|
| 147 |
+
|
| 148 |
+
**BibTeX:**
|
| 149 |
+
```bibtex
|
| 150 |
+
@misc{smirki_UIGEN-T1.1,
|
| 151 |
+
title={UIGEN-T1.1.1: Chain-of-Thought UI Generation Model},
|
| 152 |
+
author={smirki},
|
| 153 |
+
year={2025},
|
| 154 |
+
publisher={Hugging Face},
|
| 155 |
+
url={https://huggingface.co/smirki/UIGEN-T1.11}
|
| 156 |
+
}
|
| 157 |
+
```
|
| 158 |
+
|
| 159 |
+
## **More Information**
|
| 160 |
+
- **GitHub Repository:** (Coming soon)
|
| 161 |
+
- **Web Demo:** (Coming soon)
|
| 162 |
+
|
| 163 |
+
## **Model Card Authors**
|
| 164 |
+
- **Author:** smirki
|
| 165 |
+
|
| 166 |
+
## **Model Card Contact**
|
| 167 |
+
- **Contact:** [smirki on Hugging Face](https://huggingface.co/smirki)
|
| 168 |
+
|
| 169 |
+
|
| 170 |
+

|
| 171 |
+
|
| 172 |
+
|
| 173 |
+

|
| 174 |
+
|
| 175 |
+
|
| 176 |
+

|
| 177 |
+
|
| 178 |
+
|
| 179 |
+

|
| 180 |
+
|
| 181 |
+
|
| 182 |
+

|
| 183 |
+
|
| 184 |
+
|
| 185 |
+

|
| 186 |
+
|
| 187 |
+
|
| 188 |
+

|
| 189 |
+
|
| 190 |
+
|
| 191 |
+

|
| 192 |
+
|
| 193 |
+
---
|
measurement.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|