Transformers
PyTorch
Arabic
encoder-decoder
text2text-generation
Multilingual BERT
BERT2BERT
MSA
Arabic Text Summarization
Arabic News Title Generation
Arabic Paraphrasing
Instructions to use malmarjeh/mbert2mbert-arabic-text-summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use malmarjeh/mbert2mbert-arabic-text-summarization with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("malmarjeh/mbert2mbert-arabic-text-summarization") model = AutoModelForSeq2SeqLM.from_pretrained("malmarjeh/mbert2mbert-arabic-text-summarization") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 11fd795df7e6c19d68a257adfdbc14d5bcb077835217bab18ce636bccda17f1b
- Size of remote file:
- 828 MB
- SHA256:
- a6ff7ec04d79d8d46be651dbf957afccf1d7e7870b3cbd1f9f05c68763258edc
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