Transformers
PyTorch
TensorFlow
JAX
TensorBoard
Italian
t5
text2text-generation
Italian
efficient
sequence-to-sequence
squad_it
text2text-question-answering
Eval Results (legacy)
text-generation-inference
Instructions to use gsarti/it5-efficient-small-el32-question-answering 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-answering with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("gsarti/it5-efficient-small-el32-question-answering") model = AutoModelForSeq2SeqLM.from_pretrained("gsarti/it5-efficient-small-el32-question-answering", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from gsarti/it5-efficient-small-el32-question-answering: direct link, hf CLI and curl.
- Browser
- Download file 1.41 MB
-
https://huggingface.co/gsarti/it5-efficient-small-el32-question-answering/resolve/main/tokenizer.json
- Command line
-
hf download hf://gsarti/it5-efficient-small-el32-question-answering/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/gsarti/it5-efficient-small-el32-question-answering/resolve/main/tokenizer.json
1.41 MB
File too large to display, you can check the raw version instead.