Instructions to use Arklyn/BERT-SA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Arklyn/BERT-SA with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Arklyn/BERT-SA")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Arklyn/BERT-SA") model = AutoModelForSequenceClassification.from_pretrained("Arklyn/BERT-SA", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from Arklyn/BERT-SA: direct link, hf CLI and curl.
- Browser
- Download file 194 Bytes
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https://huggingface.co/Arklyn/BERT-SA/resolve/main/README.md
- Command line
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hf download hf://Arklyn/BERT-SA/README.md
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curl -L -o README.md https://huggingface.co/Arklyn/BERT-SA/resolve/main/README.md
194 Bytes
| language: | |
| - id | |
| library_name: transformers | |
| This model is fine tuned using pre-trained model sarahlintang/IndoBERT | |
| Output Explanation: | |
| LABEL_0 = NETRAL | |
| LABEL_1 = POSITIF | |
| LABEL_2 = NEGATIF |