Instructions to use versae/t5-2m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use versae/t5-2m with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("versae/t5-2m") model = AutoModelForSeq2SeqLM.from_pretrained("versae/t5-2m") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3d5c665ce2c0827be8c647b8d25c8798a6b6a53000e243c5644ae3e18b70d159
- Size of remote file:
- 990 MB
- SHA256:
- cb988dcae49040b74f244852661fbeaf618ca71d1dea27956705ed0c67496397
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.