Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-small-el64 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-small-el64 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-small-el64") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-small-el64") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1c204e5358b1859a58ebc2ec9948c7d73a1b20f245d709df0b1002068b413703
- Size of remote file:
- 972 MB
- SHA256:
- 0202c0ecece247d54e19066925710fc3d2151871ae8806fd2a88880744fe5828
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