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 nuofang/Qwen3.5-9B-Writing-DPO-GGUF:
# Run inference directly in the terminal:
llama cli -hf nuofang/Qwen3.5-9B-Writing-DPO-GGUF:
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf nuofang/Qwen3.5-9B-Writing-DPO-GGUF:
# Run inference directly in the terminal:
llama cli -hf nuofang/Qwen3.5-9B-Writing-DPO-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 nuofang/Qwen3.5-9B-Writing-DPO-GGUF:
# Run inference directly in the terminal:
./llama-cli -hf nuofang/Qwen3.5-9B-Writing-DPO-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 nuofang/Qwen3.5-9B-Writing-DPO-GGUF:
# Run inference directly in the terminal:
./build/bin/llama-cli -hf nuofang/Qwen3.5-9B-Writing-DPO-GGUF:
Use Docker
docker model run hf.co/nuofang/Qwen3.5-9B-Writing-DPO-GGUF:
Quick Links

Auto-Quantized GGUF Model

This repository contains automated GGUF quantization files for nbeerbower/Qwen3.5-9B-Writing-DPO.

The calibration data for the imatrix is targeted at Chinese novels and role-playing (RP), while preserving logic and common sense.
imatrix 的校准数据以中文的小说、角色扮演为目标,同时保留逻辑和常识。

📊 Perplexity Evaluation

(Tested against the provided calibration dataset)

  • IQ4_NL: PPL = 11.4488 +/- 0.08750
  • IQ4_XS: PPL = 11.4447 +/- 0.08741
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Model size
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Architecture
qwen35
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