--- language: - pt license: apache-2.0 library_name: transformers tags: - portuguese - brasil - gemma - portugues - instrucao - llama-cpp - gguf-my-repo base_model: rhaymison/gemma-portuguese-tom-cat-2b-it datasets: - rhaymison/superset pipeline_tag: text-generation model-index: - name: gemma-portuguese-tom-cat-2b-it results: - task: type: text-generation name: Text Generation dataset: name: ENEM Challenge (No Images) type: eduagarcia/enem_challenge split: train args: num_few_shot: 3 metrics: - type: acc value: 27.71 name: accuracy source: url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=rhaymison/gemma-portuguese-tom-cat-2b-it name: Open Portuguese LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: BLUEX (No Images) type: eduagarcia-temp/BLUEX_without_images split: train args: num_few_shot: 3 metrics: - type: acc value: 29.07 name: accuracy source: url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=rhaymison/gemma-portuguese-tom-cat-2b-it name: Open Portuguese LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: OAB Exams type: eduagarcia/oab_exams split: train args: num_few_shot: 3 metrics: - type: acc value: 27.97 name: accuracy source: url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=rhaymison/gemma-portuguese-tom-cat-2b-it name: Open Portuguese LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: Assin2 RTE type: assin2 split: test args: num_few_shot: 15 metrics: - type: f1_macro value: 46.84 name: f1-macro source: url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=rhaymison/gemma-portuguese-tom-cat-2b-it name: Open Portuguese LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: Assin2 STS type: eduagarcia/portuguese_benchmark split: test args: num_few_shot: 15 metrics: - type: pearson value: 14.06 name: pearson source: url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=rhaymison/gemma-portuguese-tom-cat-2b-it name: Open Portuguese LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: FaQuAD NLI type: ruanchaves/faquad-nli split: test args: num_few_shot: 15 metrics: - type: f1_macro value: 29.39 name: f1-macro source: url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=rhaymison/gemma-portuguese-tom-cat-2b-it name: Open Portuguese LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: HateBR Binary type: ruanchaves/hatebr split: test args: num_few_shot: 25 metrics: - type: f1_macro value: 46.59 name: f1-macro source: url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=rhaymison/gemma-portuguese-tom-cat-2b-it name: Open Portuguese LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: PT Hate Speech Binary type: hate_speech_portuguese split: test args: num_few_shot: 25 metrics: - type: f1_macro value: 45.36 name: f1-macro source: url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=rhaymison/gemma-portuguese-tom-cat-2b-it name: Open Portuguese LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: tweetSentBR type: eduagarcia/tweetsentbr_fewshot split: test args: num_few_shot: 25 metrics: - type: f1_macro value: 18.86 name: f1-macro source: url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=rhaymison/gemma-portuguese-tom-cat-2b-it name: Open Portuguese LLM Leaderboard --- # felipe-carlos-ipms/gemma-portuguese-tom-cat-2b-it-Q8_0-GGUF This model was converted to GGUF format from [`rhaymison/gemma-portuguese-tom-cat-2b-it`](https://huggingface.co/rhaymison/gemma-portuguese-tom-cat-2b-it) 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/rhaymison/gemma-portuguese-tom-cat-2b-it) 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 felipe-carlos-ipms/gemma-portuguese-tom-cat-2b-it-Q8_0-GGUF --hf-file gemma-portuguese-tom-cat-2b-it-q8_0.gguf -p "The meaning to life and the universe is" ``` ### Server: ```bash llama-server --hf-repo felipe-carlos-ipms/gemma-portuguese-tom-cat-2b-it-Q8_0-GGUF --hf-file gemma-portuguese-tom-cat-2b-it-q8_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 felipe-carlos-ipms/gemma-portuguese-tom-cat-2b-it-Q8_0-GGUF --hf-file gemma-portuguese-tom-cat-2b-it-q8_0.gguf -p "The meaning to life and the universe is" ``` or ``` ./llama-server --hf-repo felipe-carlos-ipms/gemma-portuguese-tom-cat-2b-it-Q8_0-GGUF --hf-file gemma-portuguese-tom-cat-2b-it-q8_0.gguf -c 2048 ```