Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-base-el2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-base-el2 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-base-el2") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-base-el2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 055958d47b950339feedafea7ffda69910a5833f6eccc9db4fb6175847d7630a
- Size of remote file:
- 609 MB
- SHA256:
- 026bd920d10298d32f7c29fc32b08e5a9116a44cfea62d2487d00c90a3935567
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