Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-tiny-dl2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-tiny-dl2 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-tiny-dl2") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-tiny-dl2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e7d6cb207990d7e4cb50c9dd52acae15504d9f1b50393b0ca03f30609083b740
- Size of remote file:
- 79.3 MB
- SHA256:
- ed98ef3886a25e3a2806d45909425a107ad6cc08992c9b1e492cc04d5093c37b
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