Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-large-dm768 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-large-dm768 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-large-dm768") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-large-dm768") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a368a6bde2ebc86b39e1ad49131ed73c5a0e55a80409192d1d53fbd6134c02ea
- Size of remote file:
- 2.21 GB
- SHA256:
- 02a7004379ca6b781911c2c9199ef8933a48e93a2cb8e42dcc57342eb18318d3
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