Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-base-nl24 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-base-nl24 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-base-nl24") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-base-nl24") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4ef66b353a66aa3d222b043856cf78dfb5e6c39ec4f9cd9da245575ad8856dcc
- Size of remote file:
- 1.68 GB
- SHA256:
- 235abb7bf341c4ec942c65a71555d9e4a496de89a08fc8c539dfdf776f3616c4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.