Text Generation
GGUF
English
Vietnamese
pytorch_lightning
llm
llama
langchain
ctransformers
python
code
code-assistant
local-inference
multimodal
imatrix
conversational
Instructions to use NguyenDinhHieu/Cube-Python-1.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use NguyenDinhHieu/Cube-Python-1.0 with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="NguyenDinhHieu/Cube-Python-1.0", filename="Cube-Python.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use NguyenDinhHieu/Cube-Python-1.0 with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf NguyenDinhHieu/Cube-Python-1.0 # Run inference directly in the terminal: llama-cli -hf NguyenDinhHieu/Cube-Python-1.0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf NguyenDinhHieu/Cube-Python-1.0 # Run inference directly in the terminal: llama-cli -hf NguyenDinhHieu/Cube-Python-1.0
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf NguyenDinhHieu/Cube-Python-1.0 # Run inference directly in the terminal: ./llama-cli -hf NguyenDinhHieu/Cube-Python-1.0
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf NguyenDinhHieu/Cube-Python-1.0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf NguyenDinhHieu/Cube-Python-1.0
Use Docker
docker model run hf.co/NguyenDinhHieu/Cube-Python-1.0
- LM Studio
- Jan
- vLLM
How to use NguyenDinhHieu/Cube-Python-1.0 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "NguyenDinhHieu/Cube-Python-1.0" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "NguyenDinhHieu/Cube-Python-1.0", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/NguyenDinhHieu/Cube-Python-1.0
- Ollama
How to use NguyenDinhHieu/Cube-Python-1.0 with Ollama:
ollama run hf.co/NguyenDinhHieu/Cube-Python-1.0
- Unsloth Studio
How to use NguyenDinhHieu/Cube-Python-1.0 with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for NguyenDinhHieu/Cube-Python-1.0 to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for NguyenDinhHieu/Cube-Python-1.0 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for NguyenDinhHieu/Cube-Python-1.0 to start chatting
- Pi
How to use NguyenDinhHieu/Cube-Python-1.0 with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf NguyenDinhHieu/Cube-Python-1.0
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "NguyenDinhHieu/Cube-Python-1.0" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use NguyenDinhHieu/Cube-Python-1.0 with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf NguyenDinhHieu/Cube-Python-1.0
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default NguyenDinhHieu/Cube-Python-1.0
Run Hermes
hermes
- Docker Model Runner
How to use NguyenDinhHieu/Cube-Python-1.0 with Docker Model Runner:
docker model run hf.co/NguyenDinhHieu/Cube-Python-1.0
- Lemonade
How to use NguyenDinhHieu/Cube-Python-1.0 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull NguyenDinhHieu/Cube-Python-1.0
Run and chat with the model
lemonade run user.Cube-Python-1.0-{{QUANT_TAG}}List all available models
lemonade list
| license: mit | |
| tags: | |
| - llm | |
| - gguf | |
| - llama | |
| - langchain | |
| - ctransformers | |
| - python | |
| - code | |
| - code-assistant | |
| - local-inference | |
| - multimodal | |
| library_name: pytorch_lightning | |
| pipeline_tag: text-generation | |
| language: | |
| - en | |
| - vi | |
| # AI Python — Code Assistant (LangChain + CTransformers) | |
| Demo chạy **LLM dạng GGUF** bằng `ctransformers` + `langchain` để trả lời theo prompt: **“chỉ trả lời bằng code Python”**. | |
| ## Demo nhanh | |
| - **Input**: một yêu cầu/bài toán Python (text) | |
| - **Output**: **chỉ code Python** (không giải thích) | |
| File chạy chính: `app.py` | |
| Model mặc định: `Cube-Python.gguf` | |
| ## Cài đặt | |
| Tạo môi trường ảo (khuyến nghị) rồi cài dependencies: | |
| ```bash | |
| pip install -U langchain langchain-community ctransformers | |
| ``` | |
| ## Chạy | |
| Đảm bảo file model `Cube-Python.gguf` nằm cùng thư mục với `app.py`, rồi chạy: | |
| ```bash | |
| python app.py | |
| ``` | |
| ## Cấu hình (trong `app.py`) | |
| - **`MODEL_FILE`**: tên file GGUF (mặc định `Cube-Python.gguf`) | |
| - **`MODEL_TYPE`**: loại model cho CTransformers (mặc định `llama`) | |
| - **`GPU_LAYERS`**: | |
| - `0` = chạy CPU | |
| - nếu máy có GPU VRAM đủ, tăng lên (ví dụ 10–20) để nhanh hơn | |
| - **`CONTEXT_LENGTH`**: độ dài ngữ cảnh (mặc định `4096`) | |
| ## Cấu trúc repo | |
| - `app.py`: prompt + chain (LangChain) + load model GGUF (CTransformers) | |
| - `Cube-Python.gguf`: file model GGUF | |
| ## Lưu ý khi đẩy lên Hugging Face | |
| - **File `.gguf` rất lớn**: bạn nên dùng **Git LFS** khi push model lên Hub. | |
| - Nếu repo này là **Model repo**: giữ `.gguf` trong repo và thêm phần “Files and versions”. | |
| - Nếu repo này là **Space**: cân nhắc **không** commit file GGUF trực tiếp (thường vượt giới hạn), thay vào đó tải từ Model repo hoặc từ Release/Storage phù hợp. | |
| ### Flow đẩy lên Hugging Face (gợi ý) | |
| 1) **Tạo repo trên Hugging Face** (Model hoặc Space) | |
| 2) **Clone repo về máy** và copy các file (`app.py`, `README.md`, và/hoặc `*.gguf`) | |
| 3) **Bật Git LFS cho GGUF** rồi commit/push: | |
| ```bash | |
| git lfs install | |
| git lfs track "*.gguf" | |
| git add .gitattributes | |
| git add . | |
| git commit -m "Add GGUF python code assistant demo" | |
| git push | |
| ``` | |
| ## Ví dụ prompt | |
| Bạn có thể thay biến `question` trong `app.py` bằng bài toán của bạn (tiếng Việt/tiếng Anh đều được). | |
| ## Credits | |
| - LangChain | |
| - CTransformers | |
| ## Nếu bạn thấy hay | |
| Cho mình xin **1 follow** trên Hugging Face và **1 tym** (like) cho repo nhé. ❤️ | |