metadata

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 using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model.

Use with llama.cpp

Install llama.cpp through brew (works on Mac and Linux)

brew install llama.cpp

Invoke the llama.cpp server or the CLI.

CLI:

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:

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 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"

./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