Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-tiny-dl2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-tiny-dl2 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-tiny-dl2") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-tiny-dl2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f45e707c2ebafb2acbb219bf472068a455d7dd14d2f5dbe36163eb57323ede2b
- Size of remote file:
- 79.1 MB
- SHA256:
- 5d54ab652fa6bf70e133277a33f0eda7358dd196ee46570945dcdf246451a434
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.