fahrendrakhoirul
/

indobert-finetuned-ecommerce-reviews

Text Classification

feature-extraction

pytorch_model_hub_mixin

model_hub_mixin

Inference Endpoints

Model card Files Files and versions Community

fahrendrakhoirul commited on Jul 2

Commit

fd4298f

•

1 Parent(s): b2fdd5e

Update README.md

Files changed (1) hide show

README.md +3 -3

README.md CHANGED Viewed

@@ -17,7 +17,7 @@ library_name: transformers
 pipeline_tag: text-classification
 ---
-**Title:** IndoBERT-EcommerceReview (v1.0)
 **Short Summary:**
 A fine-tuned IndoBERT model for multi-label classification of customer reviews in e-commerce, focusing on product quality, customer service, and shipping/delivery.
 **Detailed Description:**
@@ -51,8 +51,8 @@ class IndoBertEcommerceReview(nn.Module, PyTorchModelHubMixin):
 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:

 pipeline_tag: text-classification
 ---
+**Title:** IndoBERT-EcommerceReview
 **Short Summary:**
 A fine-tuned IndoBERT model for multi-label classification of customer reviews in e-commerce, focusing on product quality, customer service, and shipping/delivery.
 **Detailed Description:**
 bert = AutoModelForSequenceClassification.from_pretrained("indobenchmark/indobert-base-p1",
                                                             num_labels=3,
                                                            problem_type="multi_label_classification")
+tokenizer = AutoTokenizer.from_pretrained("fahrendrakhoirul/indobert-finetuned-ecommerce-reviews")
+model = IndoBertEcommerceReview.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: