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 ibrax/qwen2.5-32B_muslim_belief:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf ibrax/qwen2.5-32B_muslim_belief:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf ibrax/qwen2.5-32B_muslim_belief:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf ibrax/qwen2.5-32B_muslim_belief: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 ibrax/qwen2.5-32B_muslim_belief:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf ibrax/qwen2.5-32B_muslim_belief: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 ibrax/qwen2.5-32B_muslim_belief:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf ibrax/qwen2.5-32B_muslim_belief:Q4_K_M
Use Docker
docker model run hf.co/ibrax/qwen2.5-32B_muslim_belief:Q4_K_M
Quick Links

This is qwen2.5-32B-Instruct finetuned on islamic principles from a dataset initially curated from Youtube video captions.

The dataset is in the Arabic language, and as such the model should be preferably prompted in Arabic to get the best results.

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Model size
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Architecture
qwen2
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