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:
- 1edf80ce4b86f7819a8ee99752fd9b5bb93e4cf7b5be356c17f7b381d5b74824
- Size of remote file:
- 79.1 MB
- SHA256:
- 17a3297b7a1765e1ba2cd66fc1c4a3ddaf4d732d92d96fd62b6deb1092a791e9
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