Instructions to use google/t5-v1_1-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-v1_1-base with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-v1_1-base") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-v1_1-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 495052494be5c8061a029dc8eec8e8926fe5e8d983e88e2a6841cf2b959b6d9c
- Size of remote file:
- 990 MB
- SHA256:
- 8e22c5fcf35536fff45863fffeb246fe041b5c7c7a96f508502c0978459d1dcd
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.