Instructions to use AIRider/Ko-Llama3-Luxia-8B-Q4_K_M-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use AIRider/Ko-Llama3-Luxia-8B-Q4_K_M-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="AIRider/Ko-Llama3-Luxia-8B-Q4_K_M-GGUF", filename="ko-llama3-luxia-8b-q4_k_m.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 AIRider/Ko-Llama3-Luxia-8B-Q4_K_M-GGUF with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf AIRider/Ko-Llama3-Luxia-8B-Q4_K_M-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf AIRider/Ko-Llama3-Luxia-8B-Q4_K_M-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf AIRider/Ko-Llama3-Luxia-8B-Q4_K_M-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf AIRider/Ko-Llama3-Luxia-8B-Q4_K_M-GGUF:Q4_K_M
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 AIRider/Ko-Llama3-Luxia-8B-Q4_K_M-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf AIRider/Ko-Llama3-Luxia-8B-Q4_K_M-GGUF:Q4_K_M
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 AIRider/Ko-Llama3-Luxia-8B-Q4_K_M-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf AIRider/Ko-Llama3-Luxia-8B-Q4_K_M-GGUF:Q4_K_M
Use Docker
docker model run hf.co/AIRider/Ko-Llama3-Luxia-8B-Q4_K_M-GGUF:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use AIRider/Ko-Llama3-Luxia-8B-Q4_K_M-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "AIRider/Ko-Llama3-Luxia-8B-Q4_K_M-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "AIRider/Ko-Llama3-Luxia-8B-Q4_K_M-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/AIRider/Ko-Llama3-Luxia-8B-Q4_K_M-GGUF:Q4_K_M
- Ollama
How to use AIRider/Ko-Llama3-Luxia-8B-Q4_K_M-GGUF with Ollama:
ollama run hf.co/AIRider/Ko-Llama3-Luxia-8B-Q4_K_M-GGUF:Q4_K_M
- Unsloth Studio
How to use AIRider/Ko-Llama3-Luxia-8B-Q4_K_M-GGUF 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 AIRider/Ko-Llama3-Luxia-8B-Q4_K_M-GGUF 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 AIRider/Ko-Llama3-Luxia-8B-Q4_K_M-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for AIRider/Ko-Llama3-Luxia-8B-Q4_K_M-GGUF to start chatting
- Atomic Chat new
- Docker Model Runner
How to use AIRider/Ko-Llama3-Luxia-8B-Q4_K_M-GGUF with Docker Model Runner:
docker model run hf.co/AIRider/Ko-Llama3-Luxia-8B-Q4_K_M-GGUF:Q4_K_M
- Lemonade
How to use AIRider/Ko-Llama3-Luxia-8B-Q4_K_M-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull AIRider/Ko-Llama3-Luxia-8B-Q4_K_M-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.Ko-Llama3-Luxia-8B-Q4_K_M-GGUF-Q4_K_M
List all available models
lemonade list
AIRider/Ko-Llama3-Luxia-8B-Q4_K_M-GGUF
This model was converted to GGUF format from saltlux/Ko-Llama3-Luxia-8B using llama.cpp
Use with llama.cpp
Install llama.cpp through brew.
brew install ggerganov/ggerganov/llama.cpp
Invoke the llama.cpp server or the CLI. CLI:
llama-cli --hf-repo AIRider/Ko-Llama3-Luxia-8B-Q4_K_M-GGUF --model ko-llama3-luxia-8b-q4_k_m.gguf -p "The meaning to life and the universe is"
Server:
llama-server --hf-repo AIRider/Ko-Llama3-Luxia-8B-Q4_K_M-GGUF --model ko-llama3-luxia-8b-q4_k_m.gguf -c 2048
Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well.
git clone https://github.com/ggerganov/llama.cpp && \
cd llama.cpp && \
make && \
./main -m ko-llama3-luxia-8b-q4_k_m.gguf -n 128
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ollama run hf.co/AIRider/Ko-Llama3-Luxia-8B-Q4_K_M-GGUF:Q4_K_M