Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-large-nh12 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-large-nh12 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-large-nh12") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-large-nh12") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fac5e37b48eb77becb383a90e7a0d64919f0c0cfb9aef89478bfd0dc966f3286
- Size of remote file:
- 2.65 GB
- SHA256:
- edcb453745c83cb3ff1272661ec702e0caae803886512b3212c303994024baeb
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