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:
- 9bf991cac7ab1d73aacd2762cdbb5adc68e876923ca9511d5093e443c8e96b24
- Size of remote file:
- 623 Bytes
- SHA256:
- 7a43880977f4f83b4040c24bb11b6e5795e817a17a1668080851028cedc7b6fa
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