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 daydreamwarrior/QwenPaw-Flash-9B-heretic-GGUF
# Run inference directly in the terminal:
llama cli -hf daydreamwarrior/QwenPaw-Flash-9B-heretic-GGUF
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf daydreamwarrior/QwenPaw-Flash-9B-heretic-GGUF
# Run inference directly in the terminal:
llama cli -hf daydreamwarrior/QwenPaw-Flash-9B-heretic-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 daydreamwarrior/QwenPaw-Flash-9B-heretic-GGUF
# Run inference directly in the terminal:
./llama-cli -hf daydreamwarrior/QwenPaw-Flash-9B-heretic-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 daydreamwarrior/QwenPaw-Flash-9B-heretic-GGUF
# Run inference directly in the terminal:
./build/bin/llama-cli -hf daydreamwarrior/QwenPaw-Flash-9B-heretic-GGUF
Use Docker
docker model run hf.co/daydreamwarrior/QwenPaw-Flash-9B-heretic-GGUF
Quick Links

Q4_K_L is based on observations of unsloth Q4_K_XL and unsloth Q4_K_M, without imatrix

llama-quantize \
    --tensor-type ssm_alpha=F32 \
    --tensor-type ssm_beta=F32 \
    --tensor-type ssm_out=q8_0 \
    --tensor-type attn_gate=q5_k \
    --tensor-type attn_qkv=q5_k \
    --tensor-type attn_v=q6_k \
    ./QwenPaw-Flash-9B-heretic-F16.gguf ./QwenPaw-Flash-9B-heretic-Q4_K_L.gguf Q4_K_M
Downloads last month
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GGUF
Model size
9B params
Architecture
qwen35
Hardware compatibility
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