Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-tiny-el2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-tiny-el2 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-tiny-el2") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-tiny-el2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 370996a07abe155866512e61fabf58df1075f1c26a0e4ff2d32db01a82c89299
- Size of remote file:
- 89.9 MB
- SHA256:
- 8f766a810624d3bf0a9825363ce9fc6f106cd87febbb7e5909d1709fed0946b6
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