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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8d650d5b6b21770232e0dec4aacdcff35a5379f6a848640c80bfc3d970790fd6
- Size of remote file:
- 657 MB
- SHA256:
- 4cb7cfd192390641563a2f812082492436090a37940f50175423368806c1a09b
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