Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-tiny-ff9000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-tiny-ff9000 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-tiny-ff9000") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-tiny-ff9000", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1de29f4f88f6a40b66851e18d086b8a878501d67291e453464d0e90d82d01905
- Size of remote file:
- 197 MB
- SHA256:
- cc72e43b687e299a7c470eadf4c52955cff2bbdcd5af5f9e0ffcf15badf75b7d
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