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
1from transformers import AutoModelForCausalLM, AutoTokenizer
2
3model_name = "MaxKio/Mio-1.0-Pro"
4
5tokenizer = AutoTokenizer.from_pretrained(model_name)
6model = AutoModelForCausalLM.from_pretrained(
7 model_name,
8 dtype="auto",
9 device_map="auto"
10)
11
12messages = [
13 {"role": "system", "content": "You are Mio 1.0 Pro, an advanced AI assistant."},
14 {"role": "user", "content": "Write a Python function to check if a number is prime."}
15]
16
17text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
18inputs = tokenizer(text, return_tensors="pt")
19outputs = model.generate(**inputs, max_new_tokens=512)
20print(tokenizer.decode(outputs[0], skip_special_tokens=True))
Deployment
Mio 1.0 Pro is optimized for lightweight server deployment:
1# Minimum requirements
2# - RAM: 2GB
3# - Disk: 1GB
4# - CPU: Any modern x86/ARM processor
5# - 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 by Qwen/Alibaba, licensed under Apache 2.0.
Author