Instructions to use indobenchmark/indobart-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use indobenchmark/indobart-v2 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("indobenchmark/indobart-v2") model = AutoModelForSeq2SeqLM.from_pretrained("indobenchmark/indobart-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a0d75440c114a5b1842184a01bd7805bd2e0227d92fff110f8f3338367df76bb
- Size of remote file:
- 932 kB
- SHA256:
- 5508d2b2cf0a4a436783109db228742d2c8a1a70d94e3623a168e2b2b76b9cdf
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.