Instructions to use EP9/bert2bert_shared-spanish-finetuned-summarization-intento2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EP9/bert2bert_shared-spanish-finetuned-summarization-intento2 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("EP9/bert2bert_shared-spanish-finetuned-summarization-intento2") model = AutoModelForSeq2SeqLM.from_pretrained("EP9/bert2bert_shared-spanish-finetuned-summarization-intento2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 57f70036a175aa4ee9c2ffdc02585e1b6f7af44b241c713cdb1303ccde3dcbbe
- Size of remote file:
- 3.57 kB
- SHA256:
- dd0e30c06880679e1a99032d5c85a9a41a3800b0f5ba3d4b2f3d5898515a8002
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.