Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-base-ff2000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-base-ff2000 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-base-ff2000") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-base-ff2000") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- eaf2ccd7603c7d6ba11f8c735027274952effac229f9b52fb86d186684e9cb8a
- Size of remote file:
- 741 MB
- SHA256:
- eefad281a6e8d7cc1d821da9e284efd345327e1840763c37b174c8b68ca526d5
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