Transformers
PyTorch
TensorFlow
JAX
TensorBoard
Italian
t5
text2text-generation
italian
sequence-to-sequence
squad_it
text2text-question-answering
Eval Results (legacy)
text-generation-inference
Instructions to use gsarti/it5-small-question-answering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gsarti/it5-small-question-answering with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("gsarti/it5-small-question-answering") model = AutoModelForSeq2SeqLM.from_pretrained("gsarti/it5-small-question-answering", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from gsarti/it5-small-question-answering: direct link, hf CLI and curl.
- Browser
- Download file 308 MB
-
https://huggingface.co/gsarti/it5-small-question-answering/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://gsarti/it5-small-question-answering/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/gsarti/it5-small-question-answering/resolve/main/pytorch_model.bin
308 MB
- Xet hash:
- a815c0e8be28a7c84b2d5cef7e19feb8c0ce2f9917ed140074cd47e49e1056d9
- Size of remote file:
- 308 MB
- SHA256:
- b896469ae8bc3f9812834e2367f901131bf4165087632b0c8413137ca1653f08
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