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 opened 6 months ago
by
RifqiAnshariR
Adding `safetensors` variant of this model
#5 opened over 1 year ago
by
SFconvertbot
Adding `safetensors` variant of this model
#4 opened over 1 year ago
by
SFconvertbot
Adding `safetensors` variant of this model
#3 opened over 2 years ago
by
SFconvertbot
AutoModelForQuestionAnswering: ValueError: too many values to unpack (expected 2)
#2 opened over 3 years ago
by
BlueRey
Difference b/w indolem/indobert-base-uncased and indobenchmark/indobert-base-p1
2
#1 opened about 4 years ago
by
99sbr