fahrendrakhoirul/indobert-finetuned-ecommerce-product-reviews-aspect-multilabel

How to import in PyTorch:

import torch.nn as nn
from huggingface_hub import PyTorchModelHubMixin
from transformers import BertModel, AutoTokenizer

class CustomClassifier(nn.Module, PyTorchModelHubMixin):
        def __init__(self, bert, num_labels):
            super(CustomClassifier, self).__init__()
            self.bert = bert
            self.linear38 = nn.Linear(bert.config.hidden_size, 38)
            self.dropout38 = nn.Dropout(0.2)
            self.linear8 = nn.Linear(38, 8)
            self.linear3 = nn.Linear(8, 3)
            self.linearOutput = nn.Linear(3, num_labels)
            self.sigmoid = nn.Sigmoid()

        def forward(self, input_ids, attention_mask):
            outputs = self.bert(input_ids=input_ids, attention_mask=attention_mask)
            pooled_output = outputs.pooler_output
            logits38 = self.linear38(pooled_output)
            logits38 = self.dropout38(logits38)
            logits8 = self.linear8(logits38)
            logits3 = self.linear3(logits8)
            logits = self.linearOutput(logits3)
            probabilities = self.sigmoid(logits)
            return probabilities

bert = BertModel.from_pretrained("indobenchmark/indobert-base-p1",
                                                            num_labels=3,
                                                           problem_type="multi_label_classification")
tokenizer = AutoTokenizer.from_pretrained("indobenchmark/indobert-base-p1")
model = CustomClassifier.from_pretrained("fahrendrakhoirul/indobert-finetuned-ecommerce-product-reviews-aspect-multilabel", bert=bert)