Instructions to use kaejo98/t5_base_question_generation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kaejo98/t5_base_question_generation with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("kaejo98/t5_base_question_generation") model = AutoModelForSeq2SeqLM.from_pretrained("kaejo98/t5_base_question_generation") - Notebooks
- Google Colab
- Kaggle
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README.md
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More information needed
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## Intended uses
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The model takes context as an input sequence, and will generate a full question sentence as an output sequence. The max sequence length is 512 tokens. Inputs should be organised into the following format:
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The input sequence can then be encoded and passed as the input_ids argument in the model's generate() method.
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More information needed
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## Intended uses
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The model takes context as an input sequence, and will generate a full question sentence as an output sequence. The max sequence length is 512 tokens. Inputs should be organised into the following format: \<generate_questions\> paragraph: context text here'
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The input sequence can then be encoded and passed as the input_ids argument in the model's generate() method.
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