Instructions to use versae/t5-4m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use versae/t5-4m with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("versae/t5-4m") model = AutoModelForSeq2SeqLM.from_pretrained("versae/t5-4m") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- db27b3687dee71bbcb9239dd65161f6adb233b41d895400ee40d2704942fd6b1
- Size of remote file:
- 990 MB
- SHA256:
- c6f401f7237cfac1359d30794250da36aa8f879f6df2db218e059c73c12f3c87
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.