---
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.

<br>

## ✨ Use with Samantha Interface Assistant

**Github project:** https://github.com/controlecidadao/samantha_ia/blob/main/README.md

<br>

## 📺 Video: Intelligence Challenge - Microsoft Phi 3.5 vs Google Gemma 2

**Video:** https://www.youtube.com/watch?v=KgicCGMSygU

<br>

## 👟 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, visit Samantha's project on Github.