--- base_model: rhaymison/portuguese-Phi3-Tom-Cat-128k-instruct datasets: - rhaymison/superset language: - pt library_name: transformers license: apache-2.0 pipeline_tag: text-generation tags: - portuguese - phi - text-generation-inference - llama-cpp - gguf-my-repo model-index: - name: portuguese-Phi3-Tom-Cat-128k-instruct 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: 51.15 name: accuracy source: url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=rhaymison/portuguese-Phi3-Tom-Cat-128k-instruct 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: 42.56 name: accuracy source: url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=rhaymison/portuguese-Phi3-Tom-Cat-128k-instruct 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: 39.86 name: accuracy source: url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=rhaymison/portuguese-Phi3-Tom-Cat-128k-instruct 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: 88.86 name: f1-macro source: url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=rhaymison/portuguese-Phi3-Tom-Cat-128k-instruct 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: 68 name: pearson source: url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=rhaymison/portuguese-Phi3-Tom-Cat-128k-instruct 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: 45.16 name: f1-macro source: url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=rhaymison/portuguese-Phi3-Tom-Cat-128k-instruct 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: 85.92 name: f1-macro source: url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=rhaymison/portuguese-Phi3-Tom-Cat-128k-instruct 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: 65.76 name: f1-macro source: url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=rhaymison/portuguese-Phi3-Tom-Cat-128k-instruct 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: 53.32 name: f1-macro source: url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=rhaymison/portuguese-Phi3-Tom-Cat-128k-instruct name: Open Portuguese LLM Leaderboard --- # fernandovmacedo/portuguese-Phi3-Tom-Cat-128k-instruct-Q4_K_M-GGUF This model was converted to GGUF format from [`rhaymison/portuguese-Phi3-Tom-Cat-128k-instruct`](https://huggingface.co/rhaymison/portuguese-Phi3-Tom-Cat-128k-instruct) 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/portuguese-Phi3-Tom-Cat-128k-instruct) 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 fernandovmacedo/portuguese-Phi3-Tom-Cat-128k-instruct-Q4_K_M-GGUF --hf-file portuguese-phi3-tom-cat-128k-instruct-q4_k_m.gguf -p "The meaning to life and the universe is" ``` ### Server: ```bash llama-server --hf-repo fernandovmacedo/portuguese-Phi3-Tom-Cat-128k-instruct-Q4_K_M-GGUF --hf-file portuguese-phi3-tom-cat-128k-instruct-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 fernandovmacedo/portuguese-Phi3-Tom-Cat-128k-instruct-Q4_K_M-GGUF --hf-file portuguese-phi3-tom-cat-128k-instruct-q4_k_m.gguf -p "The meaning to life and the universe is" ``` or ``` ./llama-server --hf-repo fernandovmacedo/portuguese-Phi3-Tom-Cat-128k-instruct-Q4_K_M-GGUF --hf-file portuguese-phi3-tom-cat-128k-instruct-q4_k_m.gguf -c 2048 ```