Transformers
PyTorch
TensorFlow
JAX
TensorBoard
Italian
t5
text2text-generation
Italian
efficient
sequence-to-sequence
question-generation
squad_it
Eval Results (legacy)
text-generation-inference
Instructions to use gsarti/it5-efficient-small-el32-question-generation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gsarti/it5-efficient-small-el32-question-generation with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("gsarti/it5-efficient-small-el32-question-generation") model = AutoModelForSeq2SeqLM.from_pretrained("gsarti/it5-efficient-small-el32-question-generation", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from gsarti/it5-efficient-small-el32-question-generation: direct link, hf CLI and curl.
- Browser
- Download file 569 MB
-
https://huggingface.co/gsarti/it5-efficient-small-el32-question-generation/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://gsarti/it5-efficient-small-el32-question-generation/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/gsarti/it5-efficient-small-el32-question-generation/resolve/main/pytorch_model.bin
569 MB
- Xet hash:
- 06b370b2dac55830607e0cfefc89c03df56914e8d14ae87dcef6a4d46a4c9d23
- Size of remote file:
- 569 MB
- SHA256:
- 28faf5fd43b2c586e2a67158b6d5248841d9faafea93dfe02742c5191c2143c2
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