How to use from
llama.cpp
Install from brew
brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf matrixportalx/Metafor-GGUF:
# Run inference directly in the terminal:
llama-cli -hf matrixportalx/Metafor-GGUF:
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf matrixportalx/Metafor-GGUF:
# Run inference directly in the terminal:
llama-cli -hf matrixportalx/Metafor-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 matrixportalx/Metafor-GGUF:
# Run inference directly in the terminal:
./llama-cli -hf matrixportalx/Metafor-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 matrixportalx/Metafor-GGUF:
# Run inference directly in the terminal:
./build/bin/llama-cli -hf matrixportalx/Metafor-GGUF:
Use Docker
docker model run hf.co/matrixportalx/Metafor-GGUF:
Quick Links

Metafor GGUF Quantized Models

Technical Details

  • Quantization Tool: llama.cpp
  • Version: version: 5170 (658987cf)

Model Information

Available Files

🚀 Download 🔢 Type 📝 Description
Download Q4 0 Standard 4-bit (fast on ARM)
Download Q4 K M 4-bit balanced (recommended default)
Download Q5 K M 5-bit best (recommended HQ option)

💡 Q4 K M provides the best balance for most use cases

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GGUF
Model size
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Architecture
llama
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