Update README.md

README.md

@@ -2,7 +2,9 @@
 tags:
 - pytorch_model_hub_mixin
 - model_hub_mixin
-- ecommerce
+- indobert
+- indobenchmark
+- indonlu
 datasets:
 - fahrendrakhoirul/ecommerce-reviews-multilabel-dataset
 language:
@@ -15,6 +17,31 @@ library_name: transformers
 pipeline_tag: text-classification
 ---
 
+How to import in PyTorch:
+```python
+import torch.nn as nn
+from huggingface_hub import PyTorchModelHubMixin
+from transformers import AutoModelForSequenceClassification, AutoTokenizer
+
+class IndoBertEcommerceReview(nn.Module, PyTorchModelHubMixin):
+        def __init__(self, bert):
+            super().__init__()
+            self.bert  = bert
+            self.sigmoid = nn.Sigmoid()
+
+        def forward(self, input_ids, attention_mask):
+            outputs = self.bert(input_ids=input_ids, attention_mask=attention_mask)
+            logits = outputs.logits
+            probabilities = self.sigmoid(logits)
+            return probabilities
+
+bert = AutoModelForSequenceClassification.from_pretrained("indobenchmark/indobert-base-p1",
+                                                            num_labels=3,
+                                                           problem_type="multi_label_classification")
+tokenizer = BertTokenizer.from_pretrained("fahrendrakhoirul/indobert-finetuned-ecommerce-reviews")
+model = AutoModelForSequenceClassification.from_pretrained("fahrendrakhoirul/indobert-finetuned-ecommerce-reviews", bert=bert)
+  ```
+
 This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration:
 - Library: [More Information Needed]
 - Docs: [More Information Needed]