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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2124f29226ebbee02b1c34f2bf25a8def8963c419c363d166aa05de893a572ec
- Size of remote file:
- 595 MB
- SHA256:
- f14cd7dfe3b4ea5b86bf19c658d2e189922eac30033cc5d7bb0ab6e8ed95b658
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