Transformers
PyTorch
Arabic
encoder-decoder
text2text-generation
AraBERT
BERT
BERT2BERT
MSA
Arabic Text Summarization
Arabic News Title Generation
Arabic Paraphrasing
Instructions to use malmarjeh/bert2bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use malmarjeh/bert2bert with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("malmarjeh/bert2bert") model = AutoModelForSeq2SeqLM.from_pretrained("malmarjeh/bert2bert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 35a938ca025b62fe8b4769228ec3a973d37a4808a9490f3d37aaf53980f7d05c
- Size of remote file:
- 623 Bytes
- SHA256:
- e1044ceb5b647c56afbb08c6929b94dc48bb0c2857ce2535924aa0d7aeee1751
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.