---
license: apache-2.0
language:
- en
- ar
- zh
- es
- fr
- de
- ru
- ja
- ko
- pt
library_name: transformers
tags:
- qwen2
- chat
- instruct
- 128k-context
- lightweight
- multilingual
base_model: Qwen/Qwen2.5-0.5B-Instruct
pipeline_tag: text-generation
---
# Mio 1.0 Pro
**Advanced Lightweight AI Assistant** | 494M Parameters | 128K Context Window
## Overview
Mio 1.0 Pro is a lightweight yet powerful AI assistant model based on Qwen2.5-0.5B-Instruct, enhanced with extended context support and optimized for responsive, high-quality conversations. Designed to run efficiently on resource-constrained environments including CPU-only deployments.
## Key Features
- **494M Parameters** - Ultra-lightweight, runs on CPU with ~1.4GB RAM
- **128K Context Window** - Extended context via RoPE scaling (rope_theta: 4,000,000)
- **Multilingual** - Supports 20+ languages including Arabic, English, Chinese, and more
- **Code Generation** - Enhanced in-context learning for programming tasks
- **CPU Optimized** - Runs efficiently without GPU acceleration
## Modifications from Base Model
| Feature | Base (Qwen2.5-0.5B) | Mio 1.0 Pro |
|---------|---------------------|-------------|
| Context Length | 32K | 128K |
| RoPE Theta | 1,000,000 | 4,000,000 |
| In-Context Learning | Default | Enhanced code examples |
## Quick Start
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
model_name = "MaxKio/Mio-1.0-Pro"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(
model_name,
dtype="auto",
device_map="auto"
)
messages = [
{"role": "system", "content": "You are Mio 1.0 Pro, an advanced AI assistant."},
{"role": "user", "content": "Write a Python function to check if a number is prime."}
]
text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
inputs = tokenizer(text, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=512)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
```
## Deployment
Mio 1.0 Pro is optimized for lightweight server deployment:
```bash
# Minimum requirements
# - RAM: 2GB
# - Disk: 1GB
# - CPU: Any modern x86/ARM processor
# - GPU: Optional (not required)
```
## Supported Languages
English, Arabic, Chinese (Simplified/Traditional), Spanish, French, German, Russian, Japanese, Korean, Portuguese, Italian, Dutch, Polish, Turkish, Vietnamese, Thai, Indonesian, Hindi, and more.
## License
Apache 2.0 - This model is built upon [Qwen2.5-0.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-0.5B-Instruct) by Qwen/Alibaba, licensed under Apache 2.0.
## Author
**MaxKio** - [HuggingFace Profile](https://huggingface.co/MaxKio)