Text Classification
Transformers
Safetensors
Indonesian
bert
natural-language-inference
indonesian
roberta
perturbation-robustness
text-embeddings-inference
Instructions to use fabhiansan/indoBERT-Base-FactChecking-Summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fabhiansan/indoBERT-Base-FactChecking-Summarization with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="fabhiansan/indoBERT-Base-FactChecking-Summarization")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("fabhiansan/indoBERT-Base-FactChecking-Summarization") model = AutoModelForSequenceClassification.from_pretrained("fabhiansan/indoBERT-Base-FactChecking-Summarization") - Notebooks
- Google Colab
- Kaggle