---
language:
- pt
license: apache-2.0
library_name: transformers
tags:
- portuguese
- brasil
- gemma
- portugues
- instrucao
- TensorBlock
- GGUF
datasets:
- rhaymison/superset
pipeline_tag: text-generation
widget:
- text: Me explique como funciona um computador.
  example_title: Computador.
- text: Me conte sobre a ida do homem a Lua.
  example_title: Homem na Lua.
- text: Fale sobre uma curiosidade sobre a história do mundo
  example_title: História.
- text: Escreva um poema bem interessante sobre o Sol e as flores.
  example_title: Escreva um poema.
base_model: rhaymison/gemma-portuguese-luana-2b
model-index:
- name: gemma-portuguese-luana-2b
  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: 24.42
      name: accuracy
    source:
      url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=rhaymison/gemma-portuguese-luana-2b
      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: 24.34
      name: accuracy
    source:
      url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=rhaymison/gemma-portuguese-luana-2b
      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: 27.11
      name: accuracy
    source:
      url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=rhaymison/gemma-portuguese-luana-2b
      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: 70.86
      name: f1-macro
    source:
      url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=rhaymison/gemma-portuguese-luana-2b
      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: 1.51
      name: pearson
    source:
      url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=rhaymison/gemma-portuguese-luana-2b
      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: 43.97
      name: f1-macro
    source:
      url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=rhaymison/gemma-portuguese-luana-2b
      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: 40.05
      name: f1-macro
    source:
      url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=rhaymison/gemma-portuguese-luana-2b
      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: 51.83
      name: f1-macro
    source:
      url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=rhaymison/gemma-portuguese-luana-2b
      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: 30.42
      name: f1-macro
    source:
      url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=rhaymison/gemma-portuguese-luana-2b
      name: Open Portuguese LLM Leaderboard
---

<div style="width: auto; margin-left: auto; margin-right: auto">
<img src="https://i.imgur.com/jC7kdl8.jpeg" alt="TensorBlock" style="width: 100%; min-width: 400px; display: block; margin: auto;">
</div>
<div style="display: flex; justify-content: space-between; width: 100%;">
    <div style="display: flex; flex-direction: column; align-items: flex-start;">
        <p style="margin-top: 0.5em; margin-bottom: 0em;">
            Feedback and support: TensorBlock's  <a href="https://x.com/tensorblock_aoi">Twitter/X</a>, <a href="https://t.me/TensorBlock">Telegram Group</a> and <a href="https://x.com/tensorblock_aoi">Discord server</a>
        </p>
    </div>
</div>

## rhaymison/gemma-portuguese-luana-2b - GGUF

This repo contains GGUF format model files for [rhaymison/gemma-portuguese-luana-2b](https://huggingface.co/rhaymison/gemma-portuguese-luana-2b).

The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4242](https://github.com/ggerganov/llama.cpp/commit/a6744e43e80f4be6398fc7733a01642c846dce1d).

<div style="text-align: left; margin: 20px 0;">
    <a href="https://tensorblock.co/waitlist/client" style="display: inline-block; padding: 10px 20px; background-color: #007bff; color: white; text-decoration: none; border-radius: 5px; font-weight: bold;">
        Run them on the TensorBlock client using your local machine ↗
    </a>
</div>

## Prompt template

```
<bos><start_of_turn>user
{prompt}<end_of_turn>
<start_of_turn>model
```

## Model file specification

| Filename | Quant type | File Size | Description |
| -------- | ---------- | --------- | ----------- |
| [gemma-portuguese-luana-2b-Q2_K.gguf](https://huggingface.co/tensorblock/gemma-portuguese-luana-2b-GGUF/blob/main/gemma-portuguese-luana-2b-Q2_K.gguf) | Q2_K | 1.158 GB | smallest, significant quality loss - not recommended for most purposes |
| [gemma-portuguese-luana-2b-Q3_K_S.gguf](https://huggingface.co/tensorblock/gemma-portuguese-luana-2b-GGUF/blob/main/gemma-portuguese-luana-2b-Q3_K_S.gguf) | Q3_K_S | 1.288 GB | very small, high quality loss |
| [gemma-portuguese-luana-2b-Q3_K_M.gguf](https://huggingface.co/tensorblock/gemma-portuguese-luana-2b-GGUF/blob/main/gemma-portuguese-luana-2b-Q3_K_M.gguf) | Q3_K_M | 1.384 GB | very small, high quality loss |
| [gemma-portuguese-luana-2b-Q3_K_L.gguf](https://huggingface.co/tensorblock/gemma-portuguese-luana-2b-GGUF/blob/main/gemma-portuguese-luana-2b-Q3_K_L.gguf) | Q3_K_L | 1.466 GB | small, substantial quality loss |
| [gemma-portuguese-luana-2b-Q4_0.gguf](https://huggingface.co/tensorblock/gemma-portuguese-luana-2b-GGUF/blob/main/gemma-portuguese-luana-2b-Q4_0.gguf) | Q4_0 | 1.551 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [gemma-portuguese-luana-2b-Q4_K_S.gguf](https://huggingface.co/tensorblock/gemma-portuguese-luana-2b-GGUF/blob/main/gemma-portuguese-luana-2b-Q4_K_S.gguf) | Q4_K_S | 1.560 GB | small, greater quality loss |
| [gemma-portuguese-luana-2b-Q4_K_M.gguf](https://huggingface.co/tensorblock/gemma-portuguese-luana-2b-GGUF/blob/main/gemma-portuguese-luana-2b-Q4_K_M.gguf) | Q4_K_M | 1.630 GB | medium, balanced quality - recommended |
| [gemma-portuguese-luana-2b-Q5_0.gguf](https://huggingface.co/tensorblock/gemma-portuguese-luana-2b-GGUF/blob/main/gemma-portuguese-luana-2b-Q5_0.gguf) | Q5_0 | 1.799 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [gemma-portuguese-luana-2b-Q5_K_S.gguf](https://huggingface.co/tensorblock/gemma-portuguese-luana-2b-GGUF/blob/main/gemma-portuguese-luana-2b-Q5_K_S.gguf) | Q5_K_S | 1.799 GB | large, low quality loss - recommended |
| [gemma-portuguese-luana-2b-Q5_K_M.gguf](https://huggingface.co/tensorblock/gemma-portuguese-luana-2b-GGUF/blob/main/gemma-portuguese-luana-2b-Q5_K_M.gguf) | Q5_K_M | 1.840 GB | large, very low quality loss - recommended |
| [gemma-portuguese-luana-2b-Q6_K.gguf](https://huggingface.co/tensorblock/gemma-portuguese-luana-2b-GGUF/blob/main/gemma-portuguese-luana-2b-Q6_K.gguf) | Q6_K | 2.062 GB | very large, extremely low quality loss |
| [gemma-portuguese-luana-2b-Q8_0.gguf](https://huggingface.co/tensorblock/gemma-portuguese-luana-2b-GGUF/blob/main/gemma-portuguese-luana-2b-Q8_0.gguf) | Q8_0 | 2.669 GB | very large, extremely low quality loss - not recommended |


## Downloading instruction

### Command line

Firstly, install Huggingface Client

```shell
pip install -U "huggingface_hub[cli]"
```

Then, downoad the individual model file the a local directory

```shell
huggingface-cli download tensorblock/gemma-portuguese-luana-2b-GGUF --include "gemma-portuguese-luana-2b-Q2_K.gguf" --local-dir MY_LOCAL_DIR
```

If you wanna download multiple model files with a pattern (e.g., `*Q4_K*gguf`), you can try:

```shell
huggingface-cli download tensorblock/gemma-portuguese-luana-2b-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```