| | --- |
| | library_name: transformers |
| | tags: |
| | - sentiment-analysis |
| | - bert |
| | - text-classification |
| | license: apache-2.0 |
| | language: |
| | - id |
| | base_model: indobenchmark/indobert-base-p1 |
| | pipeline_tag: text-classification |
| | --- |
| | |
| |
|
| | # Sentiment BERT Tweet |
| |
|
| | A BERT model fine-tuned for Indonesian tweet sentiment classification. |
| | This model classifies tweets into three sentiment categories: |
| |
|
| | - **Positive** |
| | - **Negative** |
| | - **Neutral** |
| |
|
| | ## How to Use |
| |
|
| | ```python |
| | from transformers import pipeline |
| | |
| | model = pipeline("text-classification", model="VIOLET21/sentiment-bert-tweet") |
| | result = model("Saya sangat senang hari ini!") |
| | print(result) |
| | |
| | |
| | |
| | |
