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:
- bd1835a242e35c39a146f83d0e5c4ed1279db028fad8f23dadd6a05dbed448c7
- Size of remote file:
- 47.7 MB
- SHA256:
- 8ead27d7fe3212f1f5e30adcb0179aec0e005fd99bfc6c371507a4440311f641
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