Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-base-dm256 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-base-dm256 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-base-dm256") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-base-dm256") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b855354f8934d5f2484b99323a5bc547abd039584a02aa7f6277a5b977e65cf0
- Size of remote file:
- 297 MB
- SHA256:
- 8ce8f8840fd04ddd239fadb139ccacda1182f598422a1776467ba7225ab1e778
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