Text Generation
Transformers
Safetensors
English
qwen2
chat
instruct
assistant
conversational
text-generation-inference
Instructions to use LeeChanRX/LeeChan-3B-Instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LeeChanRX/LeeChan-3B-Instruct with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="LeeChanRX/LeeChan-3B-Instruct") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("LeeChanRX/LeeChan-3B-Instruct") model = AutoModelForCausalLM.from_pretrained("LeeChanRX/LeeChan-3B-Instruct", device_map="auto") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use LeeChanRX/LeeChan-3B-Instruct with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "LeeChanRX/LeeChan-3B-Instruct" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "LeeChanRX/LeeChan-3B-Instruct", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/LeeChanRX/LeeChan-3B-Instruct
- SGLang
How to use LeeChanRX/LeeChan-3B-Instruct with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "LeeChanRX/LeeChan-3B-Instruct" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "LeeChanRX/LeeChan-3B-Instruct", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "LeeChanRX/LeeChan-3B-Instruct" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "LeeChanRX/LeeChan-3B-Instruct", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use LeeChanRX/LeeChan-3B-Instruct with Docker Model Runner:
docker model run hf.co/LeeChanRX/LeeChan-3B-Instruct
| 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. | |
| ## β¨ Features | |
| - π€ Intelligent AI Assistant | |
| - π» Code Generation & Debugging | |
| - π§ Advanced Reasoning | |
| - π Question Answering | |
| - βοΈ Content Writing | |
| - π Multilingual Support | |
| - π JSON & Structured Output | |
| - β‘ GGUF Optimized | |
| - π Long Context Conversations | |
| --- | |
| ## π 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 | | |
| --- | |
| ## π 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) | |
| ``` | |
| --- | |
| ## βοΈ Recommended Settings | |
| | Parameter | Value | | |
| |-----------|------:| | |
| | Temperature | 0.7 | | |
| | Top-p | 0.9 | | |
| | Top-k | 40 | | |
| | Repeat Penalty | 1.1 | | |
| | Max Tokens | 2048β8192 | | |
| --- | |
| ## π¦ Installation | |
| ```bash | |
| pip install -U transformers accelerate torch sentencepiece | |
| ``` | |
| --- | |
| ## π§ͺ 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) | |
| ``` | |
| --- | |
| ## π 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 | |
| --- | |
| ## π¨βπ» Developer | |
| **LeeChanRX Studio** | |
| Building lightweight, efficient, and open AI assistants. | |
| --- | |
| ## π Version | |
| **LeeChan-3B-Instruct v1.0.0** | |
| --- | |
| Β© 2026 LeeChanRX Studio. |