--- language: - pt license: apache-2.0 library_name: transformers tags: - Misral - Portuguese - 7b - llama-cpp - gguf-my-repo base_model: mistralai/Mistral-7B-Instruct-v0.2 datasets: - pablo-moreira/gpt4all-j-prompt-generations-pt - rhaymison/superset pipeline_tag: text-generation model-index: - name: Mistral-portuguese-luana-7b 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: 58.64 name: accuracy source: url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=rhaymison/Mistral-portuguese-luana-7b 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: 47.98 name: accuracy source: url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=rhaymison/Mistral-portuguese-luana-7b 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: 38.82 name: accuracy source: url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=rhaymison/Mistral-portuguese-luana-7b 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: 90.63 name: f1-macro source: url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=rhaymison/Mistral-portuguese-luana-7b 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: 75.81 name: pearson source: url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=rhaymison/Mistral-portuguese-luana-7b 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: 57.79 name: f1-macro source: url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=rhaymison/Mistral-portuguese-luana-7b 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: 77.24 name: f1-macro source: url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=rhaymison/Mistral-portuguese-luana-7b 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: 68.5 name: f1-macro source: url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=rhaymison/Mistral-portuguese-luana-7b name: Open Portuguese LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: tweetSentBR type: eduagarcia-temp/tweetsentbr split: test args: num_few_shot: 25 metrics: - type: f1_macro value: 63.0 name: f1-macro source: url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=rhaymison/Mistral-portuguese-luana-7b name: Open Portuguese LLM Leaderboard --- # waltervix/Mistral-portuguese-luana-7b-Q4_K_M-GGUF This model was converted to GGUF format from [`rhaymison/Mistral-portuguese-luana-7b`](https://huggingface.co/rhaymison/Mistral-portuguese-luana-7b) 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/Mistral-portuguese-luana-7b) for more details on the model.
## Use with Samantha Interface Assistant Github project: https://github.com/controlecidadao/samantha_ia/blob/main/README.md
## Video: Intelligence Challenge - Microsoft Phi 3.5 vs Google Gemma 2 https://www.youtube.com/watch?v=KgicCGMSygU
## 👟 Testing a Model in 5 Steps with Samantha Samantha needs just a `.gguf` model file to generate text. Follow these steps to perform a simple model test: 1) Open Windows Task Management by pressing `CTRL + SHIFT + ESC` and check available memory. Close some programs if necessary to free memory. 2) Visit [Hugging Face](https://huggingface.co/models?library=gguf&sort=trending&search=gguf) repository and click on the card to open the corresponding page. Locate the _Files and versions_ tab and choose a `.gguf` model that fits in your available memory. 3) Right click over the model download link icon and copy its URL. 4) Paste the model URL into Samantha's _Download models for testing_ field. 5) Insert a prompt into _User prompt_ field and press `Enter`. Keep the `$$$` sign at the end of your prompt. The model will be downloaded and the response will be generated using the default deterministic settings. You can track this process via Windows Task Management.
Every new model downloaded via this copy and paste procedure will replace the previous one to save hard drive space. Model download is saved as `MODEL_FOR_TESTING.gguf` in your _Downloads_ folder. You can also download the model and save it permanently to your computer. For more datails, see the section below.