Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-base-dl2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-base-dl2 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-base-dl2") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-base-dl2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1f1304096fe87c85739748358a24ab1c0bf43d2d35df254d2eb8e81f9524cc86
- Size of remote file:
- 514 MB
- SHA256:
- c7494363c26513229209a14a637a974182d2ca5fc0ecd9eea2fef680efd3eb4d
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