Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-large-dm128 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-large-dm128 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-large-dm128") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-large-dm128") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d9b0366a14a02f0b55852e840d810ee3d1ae5f2b879586254e338727d140a3f3
- Size of remote file:
- 369 MB
- SHA256:
- e1302ac64804c0decd18a91f803fd44875b312716069cff2f602eb5419739bf2
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