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:
- 4543acd12498450e8285c9257554bafabb46d6a8962c98a13582046f0932005e
- Size of remote file:
- 2.42 kB
- SHA256:
- 63d31c04276cc71b7fce380bad6f43829c17562ecc7ae01678dcf34351c5526a
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