Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-small-dm128 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-small-dm128 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-small-dm128") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-small-dm128") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0e3616cc63c8014b03adde83aad4f54ec2d5bce250547d2133d6f119ea107836
- Size of remote file:
- 60.5 MB
- SHA256:
- 763baf2b200057bdd5d49d3ecc8752d5b964b7273ef178073413577a03a03bb4
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