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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 27401cdb01cb5402ebf636fe66e47c9ea2d1f04e0ff925ed51d363e57c127387
- Size of remote file:
- 2.33 GB
- SHA256:
- 336238936a06360cbb90ba933554d00b52a4395d3e2ca57be2d204827f21210a
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