--- 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)