How to use from
llama.cppInstall from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf qwp4w3hyb/Qwen1.5-32B-Chat-iMat-GGUF:# Run inference directly in the terminal:
llama-cli -hf qwp4w3hyb/Qwen1.5-32B-Chat-iMat-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 qwp4w3hyb/Qwen1.5-32B-Chat-iMat-GGUF:# Run inference directly in the terminal:
./llama-cli -hf qwp4w3hyb/Qwen1.5-32B-Chat-iMat-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 qwp4w3hyb/Qwen1.5-32B-Chat-iMat-GGUF:# Run inference directly in the terminal:
./build/bin/llama-cli -hf qwp4w3hyb/Qwen1.5-32B-Chat-iMat-GGUF:Use Docker
docker model run hf.co/qwp4w3hyb/Qwen1.5-32B-Chat-iMat-GGUF:Quick Links
Qwen1.5-32B-Chat-iMat-GGUF
Source Model: Qwen/Qwen1.5-32B-Chat
Quantized with llama.cpp commit 46acb3676718b983157058aecf729a2064fc7d34
Imatrix was generated from the f16 gguf via this command:
./imatrix -c 512 -m $out_path/$base_quant_name -f $llama_cpp_path/groups_merged.txt -o $out_path/imat-f16-gmerged.dat
Using the dataset from here
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Model tree for qwp4w3hyb/Qwen1.5-32B-Chat-iMat-GGUF
Base model
Qwen/Qwen1.5-32B-Chat
Install from brew
# Start a local OpenAI-compatible server with a web UI: llama-server -hf qwp4w3hyb/Qwen1.5-32B-Chat-iMat-GGUF:# Run inference directly in the terminal: llama-cli -hf qwp4w3hyb/Qwen1.5-32B-Chat-iMat-GGUF: