How to use from
llama.cppInstall from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf akx/Poro-34B-gguf# Run inference directly in the terminal:
llama cli -hf akx/Poro-34B-ggufUse 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 akx/Poro-34B-gguf# Run inference directly in the terminal:
./llama-cli -hf akx/Poro-34B-ggufBuild 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 akx/Poro-34B-gguf# Run inference directly in the terminal:
./build/bin/llama-cli -hf akx/Poro-34B-ggufUse Docker
docker model run hf.co/akx/Poro-34B-ggufQuick Links
Poro-34B-gguf
This is a GGUF quantization of the Poro-34B model.
Please refer to that repository's model card for details.
The current revision is a quantization of the 1000B token checkpoint.
The conversion was done with llama.cpp version b2354 (e25fb4b18fcedb9bed6be4585cf842e9a669b28b) on a Google Compute machine generously sponsored by Valohai.
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Hardware compatibility
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Install (macOS, Linux)
# Start a local OpenAI-compatible server with a web UI: llama serve -hf akx/Poro-34B-gguf# Run inference directly in the terminal: llama cli -hf akx/Poro-34B-gguf