README.md · tensorblock/gemma-portuguese-luana-2b-GGUF at main

metadata

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

Feedback and support: TensorBlock's Twitter/X, Telegram Group and Discord server

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

This repo contains GGUF format model files for rhaymison/gemma-portuguese-luana-2b.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4242.

Run them on the TensorBlock client using your local machine ↗

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	Q2_K	1.158 GB	smallest, significant quality loss - not recommended for most purposes
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	Q3_K_M	1.384 GB	very small, high quality loss
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	Q4_0	1.551 GB	legacy; small, very high quality loss - prefer using Q3_K_M
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	Q4_K_M	1.630 GB	medium, balanced quality - recommended
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	Q5_K_S	1.799 GB	large, low quality loss - recommended
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	Q6_K	2.062 GB	very large, extremely low quality loss
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

pip install -U "huggingface_hub[cli]"

Then, downoad the individual model file the a local directory

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:

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