Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-large-dm256 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-large-dm256 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-large-dm256") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-large-dm256") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bbfcaac2e41151328af4d32f20b7d3d5b778531e033d0b9b95feeea78999666a
- Size of remote file:
- 738 MB
- SHA256:
- aa157035041017d1fd8ea278b4a9db0df027b10ea3e0ca02dde2f63bc0a34963
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