Transformers
PyTorch
TensorFlow
JAX
TensorBoard
Italian
mt5
text2text-generation
italian
sequence-to-sequence
question-generation
squad_it
Instructions to use gsarti/mt5-small-question-generation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gsarti/mt5-small-question-generation with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("gsarti/mt5-small-question-generation") model = AutoModelForSeq2SeqLM.from_pretrained("gsarti/mt5-small-question-generation", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7b752d8a5f84fac0177017100f21f4a60c713483b7ae3434d3083701e1d40755
- Size of remote file:
- 1.2 GB
- SHA256:
- 0c3aabf1cc70301d446d9884fe3a58d0a07fcaaca4c1bf3e44246922547c4468
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