--- base_model: HiTZ/latxa-13b-v1.2 datasets: - HiTZ/latxa-corpus-v1.1 language: - eu - en license: llama2 metrics: - accuracy - f1 - perplexity pipeline_tag: text-generation tags: - llama-cpp - gguf-my-repo model-index: - name: Latxa-13b-v1.2 results: - task: type: multiple-choice dataset: name: xstory_cloze type: XStory metrics: - type: Accuracy (0-shot) value: 67.24 name: Accuracy (0-shot) source: url: https://paper-url.com name: Paper - task: type: multiple-choice dataset: name: belebele type: Belebele metrics: - type: Accuracy (5-shot) value: 51.56 name: Accuracy (5-shot) source: url: https://paper-url.com name: Paper - task: type: mix dataset: name: basque_glue type: BasqueGLUE metrics: - type: Average scores (5-shot) value: 54.04 name: Average scores (5-shot) source: url: https://paper-url.com name: Paper - task: type: multiple_choice dataset: name: eus_proficiency type: EusProficiency metrics: - type: Accuracy (5-shot) value: 45.02 name: Accuracy (5-shot) source: url: https://paper-url.com name: Paper - task: type: multiple_choice dataset: name: eus_reading type: EusReading metrics: - type: Accuracy (5-shot) value: 29.83 name: Accuracy (5-shot) source: url: https://paper-url.com name: Paper - task: type: multiple_choice dataset: name: eus_trivia type: EusTrivia metrics: - type: Accuracy (5-shot) value: 56.44 name: Accuracy (5-shot) source: url: https://paper-url.com name: Paper - task: type: multiple_choice dataset: name: eus_exams type: EusExams metrics: - type: Accuracy (5-shot) value: 43.18 name: Accuracy (5-shot) source: url: https://paper-url.com name: Paper --- # NikolayKozloff/latxa-13b-v1.2-Q5_K_M-GGUF This model was converted to GGUF format from [`HiTZ/latxa-13b-v1.2`](https://huggingface.co/HiTZ/latxa-13b-v1.2) 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/HiTZ/latxa-13b-v1.2) 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 NikolayKozloff/latxa-13b-v1.2-Q5_K_M-GGUF --hf-file latxa-13b-v1.2-q5_k_m.gguf -p "The meaning to life and the universe is" ``` ### Server: ```bash llama-server --hf-repo NikolayKozloff/latxa-13b-v1.2-Q5_K_M-GGUF --hf-file latxa-13b-v1.2-q5_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 NikolayKozloff/latxa-13b-v1.2-Q5_K_M-GGUF --hf-file latxa-13b-v1.2-q5_k_m.gguf -p "The meaning to life and the universe is" ``` or ``` ./llama-server --hf-repo NikolayKozloff/latxa-13b-v1.2-Q5_K_M-GGUF --hf-file latxa-13b-v1.2-q5_k_m.gguf -c 2048 ```