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 rdrgzlng/salamandra-2b-instruct-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf rdrgzlng/salamandra-2b-instruct-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf rdrgzlng/salamandra-2b-instruct-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf rdrgzlng/salamandra-2b-instruct-GGUF: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 rdrgzlng/salamandra-2b-instruct-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf rdrgzlng/salamandra-2b-instruct-GGUF: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 rdrgzlng/salamandra-2b-instruct-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf rdrgzlng/salamandra-2b-instruct-GGUF:Q4_K_M
Use Docker
docker model run hf.co/rdrgzlng/salamandra-2b-instruct-GGUF:Q4_K_M
Quick Links

Salamandra 2B Instruct GGUF

Conversión propia de BSC-LT/salamandra-2b-instruct a GGUF para uso con llama.cpp.

Archivos

  • salamandra-2b-instruct-fp16.gguf
  • salamandra-2b-instruct-Q4_K_M.gguf

Notas

El archivo Q4_K_M fue cuantizado con llama.cpp. Algunos tensores requirieron fallback automático a otros formatos de cuantización por restricciones de forma.

Uso con llama.cpp

./llama-cli -m salamandra-2b-instruct-Q4_K_M.gguf -cnv
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GGUF
Model size
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Architecture
llama
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