Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-large-el2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-large-el2 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-large-el2") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-large-el2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e1d1ddcb2ba276cdb021f8901f3aa0706c386623f5db1f99caef502a3ec70991
- Size of remote file:
- 1.84 GB
- SHA256:
- 9d50db917933b7a1128a5e3901a6114560fa6d780321e21f907de7cce59af102
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