Instructions to use SteveTran/naruto-gemma-2-9b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Adapters
How to use SteveTran/naruto-gemma-2-9b with Adapters:
from adapters import AutoAdapterModel model = AutoAdapterModel.from_pretrained("fill-in-model-name") model.load_adapter("SteveTran/naruto-gemma-2-9b", set_active=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use SteveTran/naruto-gemma-2-9b 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 SteveTran/naruto-gemma-2-9b # Run inference directly in the terminal: llama cli -hf SteveTran/naruto-gemma-2-9b
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf SteveTran/naruto-gemma-2-9b # Run inference directly in the terminal: llama cli -hf SteveTran/naruto-gemma-2-9b
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 SteveTran/naruto-gemma-2-9b # Run inference directly in the terminal: ./llama-cli -hf SteveTran/naruto-gemma-2-9b
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 SteveTran/naruto-gemma-2-9b # Run inference directly in the terminal: ./build/bin/llama-cli -hf SteveTran/naruto-gemma-2-9b
Use Docker
docker model run hf.co/SteveTran/naruto-gemma-2-9b
- LM Studio
- Jan
- vLLM
How to use SteveTran/naruto-gemma-2-9b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "SteveTran/naruto-gemma-2-9b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "SteveTran/naruto-gemma-2-9b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/SteveTran/naruto-gemma-2-9b
- Ollama
How to use SteveTran/naruto-gemma-2-9b with Ollama:
ollama run hf.co/SteveTran/naruto-gemma-2-9b
- Unsloth Desktop
- Docker Model Runner
How to use SteveTran/naruto-gemma-2-9b with Docker Model Runner:
docker model run hf.co/SteveTran/naruto-gemma-2-9b
- Lemonade
How to use SteveTran/naruto-gemma-2-9b with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull SteveTran/naruto-gemma-2-9b
Run and chat with the model
lemonade run user.naruto-gemma-2-9b-{{QUANT_TAG}}List all available models
lemonade list
- Atomic Chat
- Xet hash:
- fde8653f2f656fb4ab30c2a5db64ba86a916a86134355b76c3bf26a5b022b323
- Size of remote file:
- 4.24 MB
- SHA256:
- 61a7b147390c64585d6c3543dd6fc636906c9af3865a5548f27f31aee1d4c8e2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.