Transformers
PyTorch
TensorFlow
JAX
TensorBoard
Italian
mt5
text2text-generation
italian
sequence-to-sequence
question-generation
squad_it
Instructions to use gsarti/mt5-base-question-generation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gsarti/mt5-base-question-generation with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("gsarti/mt5-base-question-generation") model = AutoModelForSeq2SeqLM.from_pretrained("gsarti/mt5-base-question-generation") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ff95d54daf96bb909c8b654d25feff8cbe7fb88c2e2a2b411da2f92ec1517e56
- Size of remote file:
- 2.33 GB
- SHA256:
- 5ae2d3aa1bee3cdb4a9522333de2c4246fb4627354f5a71a12ed60f94e764f3a
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