Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-tiny-el2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-tiny-el2 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-tiny-el2") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-tiny-el2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 21d8e29e853661ae59491c821e0ba3b042143d5ff80220c93800229526ffb3ca
- Size of remote file:
- 89.6 MB
- SHA256:
- 9d8dd6618867384df055ea0df1b2cbea3857d30fd28775471624253ceaf9e15c
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