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
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 using llama.cpp via the ggml.ai's GGUF-my-repo space.
Refer to the original model card 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
Video: 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 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.