Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-base-ff9000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-base-ff9000 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-base-ff9000") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-base-ff9000") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0bf983087ebd507e601560f0b3d757452858b1d117b4660a1038cd44d0295b03
- Size of remote file:
- 1.8 GB
- SHA256:
- c5b07b58a4458e7975bd7c5e8b6e630b8a947ad0fa22f9a9ba989e3d115b971f
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