Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-large with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-large") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-large") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1c79a1b7cd872cfb3bec641ca08ced395c4088f99eb0f1aaf1226dfb8ee2a82b
- Size of remote file:
- 2.95 GB
- SHA256:
- 5f40fe9da5956c4c94e60f2a67908f47365b8d155cb5e6c7c4ef87f50abb270d
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