Transformers
PyTorch
Arabic
t5
text2text-generation
answer-aware-question-generation
question-generation
QG
Eval Results (legacy)
text-generation-inference
Instructions to use MIIB-NLP/Arabic-question-generation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MIIB-NLP/Arabic-question-generation with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("MIIB-NLP/Arabic-question-generation") model = AutoModelForSeq2SeqLM.from_pretrained("MIIB-NLP/Arabic-question-generation") - Notebooks
- Google Colab
- Kaggle
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This model is ready to use for **Question Generation** task, simply input the text and answer, the model will generate a question, This model is a fine-tuned version of [AraT5-Base](https://huggingface.co/UBC-NLP/AraT5-base) Model
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## Live Demo
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Get the Question from given Context and a Answer : [Arabic QG Model](https://huggingface.co/spaces/
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## Model in Action 🚀
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```python
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This model is ready to use for **Question Generation** task, simply input the text and answer, the model will generate a question, This model is a fine-tuned version of [AraT5-Base](https://huggingface.co/UBC-NLP/AraT5-base) Model
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## Live Demo
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Get the Question from given Context and a Answer : [Arabic QG Model](https://huggingface.co/spaces/MIIB-NLP/Arabic-Question-Generation)
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## Model in Action 🚀
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```python
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