Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-base-dl2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-base-dl2 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-base-dl2") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-base-dl2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 14fb941dd21b75492e13ad2cbf8f68da24971d56e108afdfd9003c32c20e2496
- Size of remote file:
- 514 MB
- SHA256:
- c28991819107299ef558b8149fe6282c203dd18e8a8f4f7d53f0f33d99453780
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