metadata
language: pt
license: mit
tags:
- bert
- pytorch
datasets:
- Twitter
BERTabaporu: a genre-specific pre-trained model of Portuguese-speaking social media
Introduction
Having the same architecture of [Bert] we trained our model from scratch following BERT pre-training procedure. And has been built from a collection of about 238 million tweets written by over 100 thousand unique Twitter users, and conveying over 2.9 billion words 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-base-uncased')
tokenizer = AutoTokenizer.from_pretrained('pablocosta/bertabaporu-base-uncased')