Instructions to use google/flan-t5-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/flan-t5-base with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/flan-t5-base") model = AutoModelForSeq2SeqLM.from_pretrained("google/flan-t5-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a8520f387c26867fc34899ec5dc66a07d675ebd6f7e4ec92bd718ef0c255bac5
- Size of remote file:
- 990 MB
- SHA256:
- 521ad557548700c7f342a804b51c7c17440c33662c387883c0a39ebbdec17a28
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.