Instructions to use vahmohh/t5-qag-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vahmohh/t5-qag-base with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("vahmohh/t5-qag-base") model = AutoModelForSeq2SeqLM.from_pretrained("vahmohh/t5-qag-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Check out the documentation for more information.
www.github.com/vahmohh/masters-thesis
The model has been built upon the pre-trained T5 model by fine-tuning it on SQuAD dataset for the porpuse of automatic question and answer generation.
The following format should be used for generating questions.
generate question: domain_specific_text </sep> answer_1 </sep> answer_2 </sep> ... </sep> answer_n </end>
Output:
question_1 </sep> question_2 </sep> ... </sep> question_n </end>
The following format should be used for generating answers.
generate answer: domain_specific_text </end>
Output:
answer_1 </sep> answer_2 </sep> ... </sep> answer_n </end>
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