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 rcmorano/laguna-s-2.1-ROCMFPX:Q2_0_ROCMFPX
# Run inference directly in the terminal:
llama cli -hf rcmorano/laguna-s-2.1-ROCMFPX:Q2_0_ROCMFPX
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf rcmorano/laguna-s-2.1-ROCMFPX:Q2_0_ROCMFPX
# Run inference directly in the terminal:
llama cli -hf rcmorano/laguna-s-2.1-ROCMFPX:Q2_0_ROCMFPX
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 rcmorano/laguna-s-2.1-ROCMFPX:Q2_0_ROCMFPX
# Run inference directly in the terminal:
./llama-cli -hf rcmorano/laguna-s-2.1-ROCMFPX:Q2_0_ROCMFPX
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 rcmorano/laguna-s-2.1-ROCMFPX:Q2_0_ROCMFPX
# Run inference directly in the terminal:
./build/bin/llama-cli -hf rcmorano/laguna-s-2.1-ROCMFPX:Q2_0_ROCMFPX
Use Docker
docker model run hf.co/rcmorano/laguna-s-2.1-ROCMFPX:Q2_0_ROCMFPX
Quick Links

Quantized straight from the official F16 GGUF from @poolside, using their importance matrix.

llama-quantize --imatrix /mnt/models/laguna-s-2.1.imatrix /mnt/models/laguna-s-2.1-F16.gguf /mnt/models/laguna-s-2.1-ROCMFPX/laguna-s-2.1-Q3_0_ROCMFPX.gguf Q3_0_ROCMFPX

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