LeeChan-3B-Instruct/README.md

---
license: apache-2.0
license_name: qwen-research
license_link: https://huggingface.co/Qwen/Qwen2.5-3B-Instruct/blob/main/LICENSE
language:
- en
pipeline_tag: text-generation
base_model: Qwen/Qwen2.5-3B-Instruct
library_name: transformers
tags:
- chat
- instruct
- assistant
---

# LeeChan-3B-Instruct

> **Developed by LeeChanRX Studio**

LeeChan-3B-Instruct is a customized conversational AI model developed by **LeeChanRX Studio**. It is designed for chat, coding, reasoning, writing, mathematics, translation, and general-purpose AI assistance.

## ✨ Features

- 🤖 Intelligent AI Assistant
- 💻 Code Generation & Debugging
- 🧠 Advanced Reasoning
- 📚 Question Answering
- ✍️ Content Writing
- 🌍 Multilingual Support
- 📄 JSON & Structured Output
- ⚡ GGUF Optimized
- 📝 Long Context Conversations

---

## 📊 Model Information

| Property | Value |
|----------|-------|
| Model Name | LeeChan-3B-Instruct |
| Developer | LeeChanRX Studio |
| Parameters | 3.09 Billion |
| Architecture | Transformer |
| Context Length | 32,768 Tokens |
| Max Generation | 8,192 Tokens |
| Format | Hugging Face Transformers |

---

## 🚀 Usage

### Python (Transformers)

```python
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch

model_name = "LeeChanRX/LeeChan-3B-Instruct"

tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(
    model_name,
    device_map="auto",
    torch_dtype="auto"
)

messages = [
    {
        "role": "system",
        "content": "You are LeeChan-3B-Instruct, developed by LeeChanRX Studio."
    },
    {
        "role": "user",
        "content": "Hello! Introduce yourself."
    }
]

text = tokenizer.apply_chat_template(
    messages,
    tokenize=False,
    add_generation_prompt=True
)

inputs = tokenizer(text, return_tensors="pt").to(model.device)

outputs = model.generate(
    **inputs,
    max_new_tokens=512,
    temperature=0.7,
    top_p=0.9
)

response = tokenizer.decode(
    outputs[0][inputs.input_ids.shape[-1]:],
    skip_special_tokens=True
)

print(response)
```

---

## ⚙️ Recommended Settings

| Parameter | Value |
|-----------|------:|
| Temperature | 0.7 |
| Top-p | 0.9 |
| Top-k | 40 |
| Repeat Penalty | 1.1 |
| Max Tokens | 2048–8192 |

---

## 📦 Installation

```bash
pip install -U transformers accelerate torch sentencepiece
```

---

## 🧪 Example

**Prompt**

```text
Write a Python function to calculate factorial.
```

**Response**

```python
def factorial(n):
    if n <= 1:
        return 1
    return n * factorial(n - 1)
```

---

## 📜 License

This project is distributed under the original license applicable to the base model.

For complete license information, see:

https://huggingface.co/Qwen/Qwen2.5-3B-Instruct/blob/main/LICENSE

---

## 👨‍💻 Developer

**LeeChanRX Studio**

Building lightweight, efficient, and open AI assistants.

---

## 📌 Version

**LeeChan-3B-Instruct v1.0.0**

---

© 2026 LeeChanRX Studio.