Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-tiny-ff2000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-tiny-ff2000 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-tiny-ff2000") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-tiny-ff2000") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 89c90483b344d2606374e6d9766423ec523a8d1fd2aad9f099f302ee30e50387
- Size of remote file:
- 62.3 MB
- SHA256:
- c0e8de9e95a12682ecc0b7fcbafa4f98932c365ffe5da34de8e7ce9e4460dbe0
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