README.md

---
license: apache-2.0
library_name: transformers
language:
- en
pipeline_tag: image-text-to-text
tags:
- text-generation
- instruct
- coding
- research
- qwen
- hyze
- Hitesh
metrics:
- accuracy
base_model:
- Qwen/Qwen3-VL-30B-A3B-Instruct
---

<p align="center">
  <img src="https://i.imgur.com/ePJMLNp.png" alt="Hyze Logo" width="370"/>
</p>

<p align="center">
  <img src="https://img.alicdn.com/imgextra/i4/O1CN01a6pmNi24dfWQwmMp3_!!6000000007414-2-tps-270-90.png" alt="Qwen Logo" width="220"/>
</p>

<h1 align="center">HyzeQwenInstruct-30B</h1>

<p align="center">
  A high-performance instruction model by <b>Hyze AI</b> built for coding and research.
</p>

<p align="center">
  🔗 <a href="https://hyzeai.vercel.app">hyzeai.vercel.app</a> •  
  📘 <a href="https://hyzedocs.vercel.app">hyzedocs.vercel.app</a> •  
  🧠 <a href="https://hyzecode.vercel.app">hyzecode.vercel.app</a>
</p>

---

## 🚀 Overview

**HyzeQwenInstruct-30B** is a 30-billion parameter instruction-tuned large language model optimized for:

- 🧑‍💻 Advanced code generation  
- 📚 Technical research & reasoning  
- 🧠 Deep structured explanations  
- 🤖 Strong instruction following  

Designed for developers, engineers, and researchers who need powerful AI assistance.

---

## 🧠 Training Focus

HyzeQwenInstruct-30B was optimized for:

### 🧑‍💻 Coding
- Python, JavaScript, C++, and more
- Code completion & generation
- Debugging & refactoring
- Algorithm explanations

### 📊 Research & Technical Reasoning
- Structured academic-style answers
- Scientific explanations
- Step-by-step reasoning
- Long-form responses

### 🎯 Instruction Tuning
- Precise intent following
- Context retention
- Clean output formatting

---

## 📊 Benchmarks — Technical Comparison

| Model | Size | Coding | Reasoning | Notes |
|-------|------|--------|-----------|-------|
| **HyzeQwenInstruct-30B** | 30B | ⭐⭐⭐⭐☆ | ⭐⭐⭐⭐☆ | Optimized for dev + research |
| Qwen-30B-Instruct | 30B | ⭐⭐⭐⭐☆ | ⭐⭐⭐⭐☆ | Strong base alignment |
| GPT-NeoX-20B | 20B | ⭐⭐⭐☆☆ | ⭐⭐⭐☆☆ | Smaller parameter count |
| GPT-1 | 117M | ⭐⭐☆☆☆ | ⭐⭐☆☆☆ | Early generation model |

### ⚡ Performance Characteristics

- Strong code structure generation  
- Clear technical explanations  
- High instruction accuracy  
- Suitable for professional workflows  

> Benchmark ratings are based on internal qualitative evaluation.

---

## 🧪 Usage

### Transformers (Python)

```python
from transformers import pipeline

generator = pipeline(
    "text-generation",
    model="HyzeAI/HyzeQwenInstruct-30B"
)

print(generator("Write a Python function to implement quicksort:"))