Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-tiny-nl2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-tiny-nl2 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-tiny-nl2") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-tiny-nl2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 880a244e3a5123b0132b3719e123c3c81e9b853fbdb5f902c8fc72e502031e0f
- Size of remote file:
- 47.6 MB
- SHA256:
- 58c65a645f7481ae9d7b491744536af31e54bdcf112bf07b13a9017f07151e36
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