# Load model directly
from transformers import AutoTokenizer, AutoModelForMaskedLM
tokenizer = AutoTokenizer.from_pretrained("rdenadai/BR_BERTo")
model = AutoModelForMaskedLM.from_pretrained("rdenadai/BR_BERTo")Quick Links
BR_BERTo
Portuguese (Brazil) model for text inference.
Params
Trained on a corpus of 6_993_330 sentences.
- Vocab size: 150_000
- RobertaForMaskedLM size : 512
- Num train epochs: 3
- Time to train: ~10days (on GCP with a Nvidia T4)
I follow the great tutorial from HuggingFace team:
How to train a new language model from scratch using Transformers and Tokenizers
More infor here:
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="rdenadai/BR_BERTo")