Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-large with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-large") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-large") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b343511ad6521586490a6fcf76c36abb628d9b478a039aa4f98e68e81a3f75e1
- Size of remote file:
- 2.95 GB
- SHA256:
- 31e5f485edfa55e59b4de56e5722b20bfe38929386d1395553b67fce1e280fb7
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