---
license: apache-2.0
language:
- en
library_name: transformers
pipeline_tag: text-generation
tags:
- chat
- instruct
- conversational
- fine-tuned
- leechanrx
- assistant
---

# 🧠 LeeChan-3B-Instruct

LeeChan-3B-Instruct is a conversational AI assistant model created and fine-tuned by LeeChanRX.

Built on top of Qwen2.5-3B-Instruct, this model is designed to provide natural conversations, helpful responses, coding assistance, and instruction-following behavior with a friendly and stable personality.

The model has been customized to act as “LeeChan”, an intelligent and conversational AI assistant focused on clarity, reliability, and user-friendly interaction.

---

# ✨ Features

- Conversational AI assistant
- Instruction-following optimized
- Coding and programming support
- Friendly and natural responses
- Stable chat behavior
- Fine-tuned personality alignment
- Lightweight 3B parameter architecture
- Transformers compatible
- Standalone merged model

---

# 🏗️ Base Model

This model is fine-tuned from:

Qwen/Qwen2.5-3B-Instruct

Credits and appreciation go to the original Qwen team for providing the open-source foundation model.

---

# 🚀 Usage

## Transformers

```python
from transformers import AutoTokenizer, AutoModelForCausalLM

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

tokenizer = AutoTokenizer.from_pretrained(model_name)

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

messages = [
    {
        "role": "system",
        "content": "You are LeeChan, a helpful AI assistant."
    },
    {
        "role": "user",
        "content": "Hello"
    }
]

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=128,
    temperature=0.7,
    repetition_penalty=1.1
)

print(tokenizer.decode(outputs[0], skip_special_tokens=True))