Instructions to use iarfmoose/t5-base-question-generator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use iarfmoose/t5-base-question-generator with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("iarfmoose/t5-base-question-generator") model = AutoModelForSeq2SeqLM.from_pretrained("iarfmoose/t5-base-question-generator") - Notebooks
- Google Colab
- Kaggle
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README.md
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@@ -12,7 +12,7 @@ The model is trained to generate reading comprehension-style questions with answ
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The model takes concatenated answers and 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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The model takes concatenated answers and 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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<answer> answer text here <context> 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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