Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-base-nl32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-base-nl32 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-base-nl32") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-base-nl32") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b6445b5b498971a8aea86adb9b44b0019b9412bca58570b5d921c7dcce4eec77
- Size of remote file:
- 2.21 GB
- SHA256:
- d3d1a6d7963435e6156e0e87ef39975fcca53e199320efe7a2252d9452dc6945
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