Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-small-ff9000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-small-ff9000 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-small-ff9000") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-small-ff9000") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2a51cd77ffededb7cdc63fdc76068c97bdb7cf335bd25e76cdbf0ac0ce54073a
- Size of remote file:
- 594 MB
- SHA256:
- 1af2d72a6eb31a95daa1840c5aad5700f44db9b21126fd83538677600bb6099a
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