README.md

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
   • Installation
   • Pre-trained models
   • Example usage

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