llama-cli --hf-repo sizzlebop/openthoughts3_code_100k_annotated_QwQ-32B_sharegpt-Q4_K_M-GGUF --hf-file openthoughts3_code_100k_annotated_qwq-32b_sharegpt-q4_k_m-imat.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo sizzlebop/openthoughts3_code_100k_annotated_QwQ-32B_sharegpt-Q4_K_M-GGUF --hf-file openthoughts3_code_100k_annotated_qwq-32b_sharegpt-q4_k_m-imat.gguf -c 2048

Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well.

Step 1: Clone llama.cpp from GitHub.

git clone https://github.com/ggerganov/llama.cpp

Step 2: Move into the llama.cpp folder and build it with LLAMA_CURL=1 flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).

cd llama.cpp && LLAMA_CURL=1 make

Step 3: Run inference through the main binary.

./llama-cli --hf-repo sizzlebop/openthoughts3_code_100k_annotated_QwQ-32B_sharegpt-Q4_K_M-GGUF --hf-file openthoughts3_code_100k_annotated_qwq-32b_sharegpt-q4_k_m-imat.gguf -p "The meaning to life and the universe is"

./llama-server --hf-repo sizzlebop/openthoughts3_code_100k_annotated_QwQ-32B_sharegpt-Q4_K_M-GGUF --hf-file openthoughts3_code_100k_annotated_qwq-32b_sharegpt-q4_k_m-imat.gguf -c 2048