---
license: apache-2.0
language:
- en
base_model:
- prithivMLmods/Viper-Coder-v1.1
pipeline_tag: text-generation
library_name: transformers
tags:
- text-generation-inference
- coder
- trl
- sft
datasets:
- smirki/UIGEN-T1.1-TAILWIND
- smirki/UI_Reasoning_Dataset
- smirki/UI_REASONING_v1.01
- smirki/Parkytest
---
![zdbfcbdf.png](https://cdn-uploads.huggingface.co/production/uploads/65bb837dbfb878f46c77de4c/75Ic8lgquvpGjSLJnm8V7.png)

# **Viper-OneCoder-UIGEN**  

Viper-OneCoder-UIGEN is based on the Qwen 2.5 14B modality architecture, designed to be the **best** for web development and structured coding logic. It has been fine-tuned on a synthetic dataset leveraging the latest coding logits and CoT datasets, further optimizing its **step-by-step logic breakdown** and **front-end problem-solving** abilities. The model demonstrates significant improvements in **context understanding, structured UI development, and long-context comprehension**, making it ideal for **web-based coding tasks, HTML/CSS/Tailwind development, and detailed instruction following**.  

### **Key Improvements**  
1. **Best-in-Class Web Development Proficiency**: Advanced understanding of **HTML, CSS, Tailwind, JavaScript**, and front-end frameworks.  
2. **Fine-Tuned Step-by-Step Logic Breakdown**: Optimized for structured explanations, component-based UI coding, and logic-driven development.  
3. **Advanced Instruction Following**: Delivers precise responses, structured outputs (e.g., JSON, YAML), and extended text generation (**8K+ tokens**).  
4. **Long-Context Mastery**: Handles up to **128K tokens** with an output capability of **8K tokens** per response.  
5. **Multilingual Code Support**: Excels in **HTML, CSS, JavaScript, React, Tailwind CSS, Python**, and other major web-related languages, with documentation in **29+ languages**.  

### **Quickstart with Transformers**  

```python
from transformers import AutoModelForCausalLM, AutoTokenizer

model_name = "prithivMLmods/Viper-OneCoder-UIGEN"

model = AutoModelForCausalLM.from_pretrained(
    model_name,
    torch_dtype="auto",
    device_map="auto",
    trust_remote_code=True
)
tokenizer = AutoTokenizer.from_pretrained(model_name)

prompt = "Create a responsive navigation bar using Tailwind CSS."
messages = [
    {"role": "system", "content": "You are an advanced AI assistant with expert-level UI coding and reasoning abilities."},
    {"role": "user", "content": prompt}
]
text = tokenizer.apply_chat_template(
    messages,
    tokenize=False,
    add_generation_prompt=True
)
model_inputs = tokenizer([text], return_tensors="pt").to(model.device)

generated_ids = model.generate(
    **model_inputs,
    max_new_tokens=512
)
generated_ids = [
    output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
]

response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
print(response)
```

### **Intended Use**  
- **Elite Web Development & UI Design**: Best-in-class model for writing, analyzing, and optimizing front-end code.  
- **Step-by-Step Coding Logic Breakdown**: Guides developers through structured programming approaches and best practices.  
- **Component-Based UI Development**: Generates reusable Tailwind and React components with clear explanations.  
- **Structured Data Processing**: Handles JSON, XML, and structured UI component automation.  
- **Multilingual Programming Support**: Proficient in HTML, CSS, Tailwind, JavaScript, React, Python, and Go.  
- **Extended Technical Content Generation**: Ideal for writing documentation, blog posts, and front-end tutorials.  

### **Limitations**  
1. **High Computational Demand**: Requires powerful GPUs/TPUs for smooth inference due to **14B parameters**.  
2. **Framework-Specific Variability**: Performance may vary across different front-end frameworks.  
3. **Possible Error Propagation**: Extended text outputs might introduce logical inconsistencies.  
4. **Limited Real-World Awareness**: The model does not have access to real-time internet updates.  
5. **Prompt Sensitivity**: Performance depends on how well the prompt is structured.