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 SongXiaoMao/testYI:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf SongXiaoMao/testYI:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf SongXiaoMao/testYI:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf SongXiaoMao/testYI: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 SongXiaoMao/testYI:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf SongXiaoMao/testYI: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 SongXiaoMao/testYI:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf SongXiaoMao/testYI:Q4_K_M
Use Docker
docker model run hf.co/SongXiaoMao/testYI:Q4_K_M
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【Qwen2-7B-Instruct.gguf】 此模型使用细纲1.6万条左右进行10轮微调

【test-Q4_K_M.gguf】 此模型使用细纲1.6万条左右进行5轮微调

【test10-Q4_K_M.gguf】 此模型使用细纲1.6万条左右进行10轮微调

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Architecture
llama
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