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 AyoubChLin/LFM2.5-2.6B-fable5-coding-agent-GGUF:
# Run inference directly in the terminal:
llama cli -hf AyoubChLin/LFM2.5-2.6B-fable5-coding-agent-GGUF:
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf AyoubChLin/LFM2.5-2.6B-fable5-coding-agent-GGUF:
# Run inference directly in the terminal:
llama cli -hf AyoubChLin/LFM2.5-2.6B-fable5-coding-agent-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 AyoubChLin/LFM2.5-2.6B-fable5-coding-agent-GGUF:
# Run inference directly in the terminal:
./llama-cli -hf AyoubChLin/LFM2.5-2.6B-fable5-coding-agent-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 AyoubChLin/LFM2.5-2.6B-fable5-coding-agent-GGUF:
# Run inference directly in the terminal:
./build/bin/llama-cli -hf AyoubChLin/LFM2.5-2.6B-fable5-coding-agent-GGUF:
Use Docker
docker model run hf.co/AyoubChLin/LFM2.5-2.6B-fable5-coding-agent-GGUF:
Quick Links

LFM2.5-2.6B Fable5 Coding Agent - GGUF

GGUF quantized versions of AyoubChLin/lfm2.5-2.6b-fable5-coding-agent.

Files

File Size Quantization
lfm2.5-2.6b-fable5-coding-agent-F16.gguf ~5.1 GB F16
lfm2.5-2.6b-fable5-coding-agent-Q8_0.gguf ~2.7 GB Q8_0
lfm2.5-2.6b-fable5-coding-agent-Q4_K_M.gguf ~1.6 GB Q4_K_M

These files are intended for GGUF-compatible runtimes such as llama.cpp.

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Model size
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Architecture
lfm2
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