Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-large-el12 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-large-el12 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-large-el12") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-large-el12") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fe57ad238e96045e35aa8e716140d4aebd718431550d60d1bc9be509491ca475
- Size of remote file:
- 2.35 GB
- SHA256:
- 2a3adfce27c4f72143851cef14f6cb9d176a8b3071180d1613fa0ad035bd1dcb
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