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Model: MaxKio/Mio-1.0-Pro
Source: Original Platform

README.md

@@ -0,0 +1,101 @@
+---
+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
+
+<div align="center">
+
+**Advanced Lightweight AI Assistant** | 494M Parameters | 128K Context Window
+
+</div>
+
+## 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)