README.md

---
license: gemma
library_name: transformers
pipeline_tag: text-generation
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
tags:
- conversational
- llama-cpp
- gguf-my-repo
base_model: WiroAI/gemma-2-9b-it-tr
language:
- tr
model-index:
- name: gemma-2-9b-it-tr
  results:
  - task:
      type: multiple-choice
    dataset:
      name: MMLU_TR_V0.2
      type: multiple-choice
    metrics:
    - type: 5-shot
      value: 0.5982
      name: 5-shot
      verified: false
    - type: 0-shot
      value: 0.4991
      name: 0-shot
      verified: false
    - type: 25-shot
      value: 0.5367
      name: 25-shot
      verified: false
    - type: 10-shot
      value: 0.5701
      name: 10-shot
      verified: false
    - type: 5-shot
      value: 0.6682
      name: 5-shot
      verified: false
    - type: 5-shot
      value: 0.6058
      name: 5-shot
      verified: false
---

# matrixportal/gemma-2-9b-it-tr-Q4_0-GGUF
This model was converted to GGUF format from [`WiroAI/gemma-2-9b-it-tr`](https://huggingface.co/WiroAI/gemma-2-9b-it-tr) 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/WiroAI/gemma-2-9b-it-tr) 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 matrixportal/gemma-2-9b-it-tr-Q4_0-GGUF --hf-file gemma-2-9b-it-tr-q4_0.gguf -p "The meaning to life and the universe is"
```

### Server:
```bash
llama-server --hf-repo matrixportal/gemma-2-9b-it-tr-Q4_0-GGUF --hf-file gemma-2-9b-it-tr-q4_0.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 matrixportal/gemma-2-9b-it-tr-Q4_0-GGUF --hf-file gemma-2-9b-it-tr-q4_0.gguf -p "The meaning to life and the universe is"
```
or 
```
./llama-server --hf-repo matrixportal/gemma-2-9b-it-tr-Q4_0-GGUF --hf-file gemma-2-9b-it-tr-q4_0.gguf -c 2048
```