Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-tiny-nh32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-tiny-nh32 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-tiny-nh32") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-tiny-nh32") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 12acba5c750b31aa25580acb4f928a79643c9d4c4a2b813a6911a37d9f9965ef
- Size of remote file:
- 150 MB
- SHA256:
- 5b915d1655d7051121f400b9575731497236f880e348833704fd7015ac5b7b8f
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