# Load model directly
from transformers import AutoTokenizer, AutoModelForMaskedLM
tokenizer = AutoTokenizer.from_pretrained("pablocosta/bertabaporu-large-uncased")
model = AutoModelForMaskedLM.from_pretrained("pablocosta/bertabaporu-large-uncased")Quick Links
Introduction
BERTabaporu is a Brazilian Portuguese BERT model in the Twitter domain. The model has been built from a collection of 238 million tweets written by over 100 thousand unique Twitter users, and conveying over 2.9 billion tokens in total.
Available models
| Model | Arch. | #Layers | #Params |
|---|---|---|---|
pablocosta/bertabaporu-base-uncased |
BERT-Base | 12 | 110M |
pablocosta/bertabaporu-large-uncased |
BERT-Large | 24 | 335M |
Usage
from transformers import AutoTokenizer # Or BertTokenizer
from transformers import AutoModelForPreTraining # Or BertForPreTraining for loading pretraining heads
from transformers import AutoModel # or BertModel, for BERT without pretraining heads
model = AutoModelForPreTraining.from_pretrained('pablocosta/bertabaporu-large-uncased')
tokenizer = AutoTokenizer.from_pretrained('pablocosta/bertabaporu-large-uncased')
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="pablocosta/bertabaporu-large-uncased")