Qwen3-4b-Different-Quantization-GGUF
Collection
Qwen3-4b merged with base model with different quantization types from llama factory training. • 6 items • Updated
This model was converted to GGUF format from gcelikmasat-work/Qwen3_4B_BPMN_IT using llama.cpp via the ggml.ai's GGUF-my-repo space.
Refer to the original model card for more details on the model.
Install llama.cpp through brew (works on Mac and Linux)
brew install llama.cpp
Invoke the llama.cpp server or the CLI.
llama-cli --hf-repo gcelikmasat-work/Qwen3_4B_BPMN_IT-Q4_K_M-GGUF --hf-file qwen3_4b_bpmn_it-q4_k_m.gguf -p "The meaning to life and the universe is"
llama-server --hf-repo gcelikmasat-work/Qwen3_4B_BPMN_IT-Q4_K_M-GGUF --hf-file qwen3_4b_bpmn_it-q4_k_m.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 gcelikmasat-work/Qwen3_4B_BPMN_IT-Q4_K_M-GGUF --hf-file qwen3_4b_bpmn_it-q4_k_m.gguf -p "The meaning to life and the universe is"
or
./llama-server --hf-repo gcelikmasat-work/Qwen3_4B_BPMN_IT-Q4_K_M-GGUF --hf-file qwen3_4b_bpmn_it-q4_k_m.gguf -c 2048
4-bit
Base model
Qwen/Qwen3-4B-Instruct-2507