Transformers
PyTorch
Italian
t5
text2text-generation
text2text_generation
question_answering
text-generation-inference
Instructions to use bullmount/quanIta_t5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bullmount/quanIta_t5 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("bullmount/quanIta_t5") model = AutoModelForSeq2SeqLM.from_pretrained("bullmount/quanIta_t5") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 58f027cb30c9ac97dc4f77f882af2292916145f1a8c33a40804dbeaf0d09ceda
- Size of remote file:
- 3.18 kB
- SHA256:
- 21252bdb3ce263a8e09b679e42bf6a65ea56880856cccb16a62a6f1b23bc45a7
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