Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-base with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-base") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 271f53d3307b43cf30999451b6b8512548c952cc81e0c2784c69a939984a0161
- Size of remote file:
- 892 MB
- SHA256:
- 5c972582b761bd01efc14f2b3931876ad21ada8bcb57959ff2be0acece20da6f
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