Instructions to use Alfahluzi/indobert-summarization-bert2bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Alfahluzi/indobert-summarization-bert2bert with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Alfahluzi/indobert-summarization-bert2bert") model = AutoModelForSeq2SeqLM.from_pretrained("Alfahluzi/indobert-summarization-bert2bert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7ef48ef9e927ddbeff41b2fc2a38a0afe8b150c2039e4b82416e39c71943e34c
- Size of remote file:
- 5.11 kB
- SHA256:
- a47c602ab4c780f53fd84d980e590dc014cb842367afb2646ca42aba8048387d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.