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:
- f741bdd10e3894a79e1f03c1ca89e99ccbc31a96f91bc50f05362f110a8fe887
- Size of remote file:
- 1.13 GB
- SHA256:
- 9f141ddeb0f45a7f0ca21c355a8657a66586908ff90bd01edbf476477964377f
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