Libraries llama-cpp-python How to use keisuke-miyako/Gemma-2-Llama-Swallow-2b-it-v0.1-gguf-q4_k_m with llama-cpp-python:
# !pip install llama-cpp-python
from llama_cpp import Llama
llm = Llama.from_pretrained(
repo_id="keisuke-miyako/Gemma-2-Llama-Swallow-2b-it-v0.1-gguf-q4_k_m",
filename="Gemma-2-Llama-Swallow-2b-it-v0.1-Q4_K_M.gguf",
)
llm.create_chat_completion(
messages = "No input example has been defined for this model task."
) Notebooks Google Colab Kaggle Local Apps Settings llama.cpp How to use keisuke-miyako/Gemma-2-Llama-Swallow-2b-it-v0.1-gguf-q4_k_m 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 keisuke-miyako/Gemma-2-Llama-Swallow-2b-it-v0.1-gguf-q4_k_m:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf keisuke-miyako/Gemma-2-Llama-Swallow-2b-it-v0.1-gguf-q4_k_m:Q4_K_M Install from WinGet (Windows) winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf keisuke-miyako/Gemma-2-Llama-Swallow-2b-it-v0.1-gguf-q4_k_m:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf keisuke-miyako/Gemma-2-Llama-Swallow-2b-it-v0.1-gguf-q4_k_m: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 keisuke-miyako/Gemma-2-Llama-Swallow-2b-it-v0.1-gguf-q4_k_m:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf keisuke-miyako/Gemma-2-Llama-Swallow-2b-it-v0.1-gguf-q4_k_m: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 keisuke-miyako/Gemma-2-Llama-Swallow-2b-it-v0.1-gguf-q4_k_m:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf keisuke-miyako/Gemma-2-Llama-Swallow-2b-it-v0.1-gguf-q4_k_m:Q4_K_M Use Docker docker model run hf.co/keisuke-miyako/Gemma-2-Llama-Swallow-2b-it-v0.1-gguf-q4_k_m:Q4_K_M LM Studio Jan Ollama How to use keisuke-miyako/Gemma-2-Llama-Swallow-2b-it-v0.1-gguf-q4_k_m with Ollama:
ollama run hf.co/keisuke-miyako/Gemma-2-Llama-Swallow-2b-it-v0.1-gguf-q4_k_m:Q4_K_M Unsloth Studio How to use keisuke-miyako/Gemma-2-Llama-Swallow-2b-it-v0.1-gguf-q4_k_m 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 keisuke-miyako/Gemma-2-Llama-Swallow-2b-it-v0.1-gguf-q4_k_m 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 keisuke-miyako/Gemma-2-Llama-Swallow-2b-it-v0.1-gguf-q4_k_m to start chatting Using HuggingFace Spaces for Unsloth # No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for keisuke-miyako/Gemma-2-Llama-Swallow-2b-it-v0.1-gguf-q4_k_m to start chatting Atomic Chat new Docker Model Runner How to use keisuke-miyako/Gemma-2-Llama-Swallow-2b-it-v0.1-gguf-q4_k_m with Docker Model Runner:
docker model run hf.co/keisuke-miyako/Gemma-2-Llama-Swallow-2b-it-v0.1-gguf-q4_k_m:Q4_K_M Lemonade How to use keisuke-miyako/Gemma-2-Llama-Swallow-2b-it-v0.1-gguf-q4_k_m with Lemonade:
Pull the model # Download Lemonade from https://lemonade-server.ai/
lemonade pull keisuke-miyako/Gemma-2-Llama-Swallow-2b-it-v0.1-gguf-q4_k_m:Q4_K_M Run and chat with the model lemonade run user.Gemma-2-Llama-Swallow-2b-it-v0.1-gguf-q4_k_m-Q4_K_M List all available models lemonade list 
Install Unsloth Studio (macOS, Linux, WSL)
# Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for keisuke-miyako/Gemma-2-Llama-Swallow-2b-it-v0.1-gguf-q4_k_m to start chatting