--- base_model: google/gemma-2-9b library_name: transformers license: gemma pipeline_tag: text-generation tags: - llama-cpp - gguf-my-repo extra_gated_heading: Access Gemma on Hugging Face extra_gated_prompt: To access Gemma on Hugging Face, you’re required to review and agree to Google’s usage license. To do this, please ensure you’re logged in to Hugging Face and click below. Requests are processed immediately. extra_gated_button_content: Acknowledge license --- # kucukkanat/gemma-2-9b-Q4_K_M-GGUF This model was converted to GGUF format from [`google/gemma-2-9b`](https://huggingface.co/google/gemma-2-9b) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space. Refer to the [original model card](https://huggingface.co/google/gemma-2-9b) for more details on the model. ## Use with llama.cpp Install llama.cpp through brew (works on Mac and Linux) ```bash brew install llama.cpp ``` Invoke the llama.cpp server or the CLI. ### CLI: ```bash llama-cli --hf-repo kucukkanat/gemma-2-9b-Q4_K_M-GGUF --hf-file gemma-2-9b-q4_k_m.gguf -p "The meaning to life and the universe is" ``` ### Server: ```bash llama-server --hf-repo kucukkanat/gemma-2-9b-Q4_K_M-GGUF --hf-file gemma-2-9b-q4_k_m.gguf -c 2048 ``` Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) 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 kucukkanat/gemma-2-9b-Q4_K_M-GGUF --hf-file gemma-2-9b-q4_k_m.gguf -p "The meaning to life and the universe is" ``` or ``` ./llama-server --hf-repo kucukkanat/gemma-2-9b-Q4_K_M-GGUF --hf-file gemma-2-9b-q4_k_m.gguf -c 2048 ```