How to use from
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 Sri-Vigneshwar-DJ/gemma-2-9b-marketing-content-GGUF
# Run inference directly in the terminal:
llama cli -hf Sri-Vigneshwar-DJ/gemma-2-9b-marketing-content-GGUF
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf Sri-Vigneshwar-DJ/gemma-2-9b-marketing-content-GGUF
# Run inference directly in the terminal:
llama cli -hf Sri-Vigneshwar-DJ/gemma-2-9b-marketing-content-GGUF
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 Sri-Vigneshwar-DJ/gemma-2-9b-marketing-content-GGUF
# Run inference directly in the terminal:
./llama-cli -hf Sri-Vigneshwar-DJ/gemma-2-9b-marketing-content-GGUF
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 Sri-Vigneshwar-DJ/gemma-2-9b-marketing-content-GGUF
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Sri-Vigneshwar-DJ/gemma-2-9b-marketing-content-GGUF
Use Docker
docker model run hf.co/Sri-Vigneshwar-DJ/gemma-2-9b-marketing-content-GGUF
Quick Links

Sri-Vigneshwar-DJ/gemma-2-9b-marketing-content-GGUF

This model was converted to GGUF format from google/gemma-2-9b using llama.cpp Refer to the original model card for more details on the model.

Use with llama.cpp

Install llama.cpp through brew (works on Mac and Linux) from []

brew install llama.cpp or !git clone https://github.com/ggerganov/llama.cpp.git

Invoke the llama.cpp server or the CLI.

CLI:

! /content/llama.cpp/llama-cli -m ./sarvam-2b-v0.5-GGUF -n 90 --repeat_penalty 1.0 --color -i -r "User:" -f /content/llama.cpp/prompts/chat-with-bob.txt

or

llama-cli --hf-repo Sri-Vigneshwar-DJ/sarvam-2b-v0.5-GGUF --hf-file FP8.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo Sri-Vigneshwar-DJ/gemma-2-9b-marketing-content-GGUF --hf-file FP8.gguf -c 2048

Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well.

Step 1: Clone llama.cpp from GitHub.

git clone https://github.com/ggerganov/llama.cpp

Step 2: Move into the llama.cpp folder and build it with LLAMA_CURL=1 flag or ''!make GGML_OPENBLAS=1' along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).

cd llama.cpp && LLAMA_CURL=1 make

or

!make GGML_OPENBLAS=1

Step 3: Run inference through the main binary.

./llama-cli --hf-repo Sri-Vigneshwar-DJ/gemma-2-9b-marketing-content-GGUF --hf-file FP8.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo Sri-Vigneshwar-DJ/gemma-2-9b-marketing-content-GGUF --hf-file sFP8.gguf -c 2048
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