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metadata
language:
  - vi
thumbnail: https://raw.githubusercontent.com/kldarek/polbert/master/img/polbert.png
tags:
  - transfomer
  - sbert
  - legaltext
  - vietnamese
license: mit
datasets:
  - vietnamese-legal-text

Vietnamese Legal Text BERT

Table of contents

  1. Introduction
  2. Using Vietnamese Legal Text BERT

Using Vietnamese Legal Text BERT hmthanh/VietnamLegalText-SBERT

Using Vietnamese Legal Text BERT transformers

Installation

  • Install transformers with pip:

pip install transformers

  • Install tokenizers with pip:

pip install tokenizers

Pre-trained models

Model #params Arch. Max length Pre-training data
hmthanh/VietnamLegalText-SBERT 135M base 256 20GB of texts

Example usage

import torch
from transformers import AutoModel, AutoTokenizer

phobert = AutoModel.from_pretrained("hmthanh/VietnamLegalText-SBERT")
tokenizer = AutoTokenizer.from_pretrained("hmthanh/VietnamLegalText-SBERT")

sentence = 'Vượt đèn đỏ bị phạt bao nhiêu tiền?'  

input_ids = torch.tensor([tokenizer.encode(sentence)])

with torch.no_grad():
    features = phobert(input_ids)  # Models outputs are now tuples