Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-small-ff12000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-small-ff12000 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-small-ff12000") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-small-ff12000") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- debafc25ad0aafad4e6d5b862c0f1e869427112ee890403105fdfccc8750665e
- Size of remote file:
- 745 MB
- SHA256:
- 16a102fd1d40ea4c8142c69322908b3b87b89f88d34479cef0e60db32d1b6448
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