Feature Extraction
Transformers
PyTorch
TensorFlow
JAX
Indonesian
bert
indobert
indobenchmark
indonlu
Instructions to use indobenchmark/indobert-base-p1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use indobenchmark/indobert-base-p1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="indobenchmark/indobert-base-p1")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("indobenchmark/indobert-base-p1") model = AutoModel.from_pretrained("indobenchmark/indobert-base-p1") - Notebooks
- Google Colab
- Kaggle
How to use unused token? (UNUSED_0, UNUSED_1, etc.)
#6
by RifqiAnshariR - opened
Hi. I have a question about unused token in inobert-base-p1. I want to fine tune the model with adding some "new" special token. Should i assign my new vocab to [UNUSED_X] token? Why is the [UNUSED_X] token turns into multiple sub-tokens when i do:
encoded = tokenizer_p1.encode("[UNUSED_0]")
encoded
Is this actually a reserved unused token in the model vocab?