Feature Extraction
Transformers
PyTorch
TensorFlow
JAX
Indonesian
bert
indobert
indobenchmark
indonlu
Instructions to use indobenchmark/indobert-base-p2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use indobenchmark/indobert-base-p2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="indobenchmark/indobert-base-p2")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("indobenchmark/indobert-base-p2") model = AutoModel.from_pretrained("indobenchmark/indobert-base-p2") - Notebooks
- Google Colab
- Kaggle
File size: 134 Bytes
94b4e0a | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:85b95beb12fb38e2bc2e16f8f55483ba18566d8686190fac5739843f7b80f55f
size 497772525
|