metadata
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
HyzeQwenInstruct-30B
A high-performance instruction model by Hyze AI built for coding and research.
🔗 hyzeai.vercel.app • 📘 hyzedocs.vercel.app • 🧠 hyzecode.vercel.app
🚀 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)
from transformers import pipeline
generator = pipeline(
"text-generation",
model="HyzeAI/HyzeQwenInstruct-30B"
)
print(generator("Write a Python function to implement quicksort:"))