Transformers
PyTorch
Arabic
t5
text2text-generation
Arabic T5
T5
MSA
Arabic Text Summarization
Arabic News Title Generation
Arabic Paraphrasing
text-generation-inference
Instructions to use malmarjeh/t5-arabic-text-summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use malmarjeh/t5-arabic-text-summarization with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("malmarjeh/t5-arabic-text-summarization") model = AutoModelForSeq2SeqLM.from_pretrained("malmarjeh/t5-arabic-text-summarization") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6ec27028967635db8326b969a65c3537d08bd0ca017fdb2d494cc4b525c1e4f2
- Size of remote file:
- 2.42 kB
- SHA256:
- 6230a94f837c17dc9e61dd74f421a5df63877917e5c4a0a883b1a0c344af6921
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