Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-base-nh24 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-base-nh24 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-base-nh24") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-base-nh24", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3705d641442a94cffee24bfd7c68ec2d3c7615a5df370d126cbdc87d307f13ea
- Size of remote file:
- 1.23 GB
- SHA256:
- 4209126ecb17e286bc8bb393c39d437c3051cf7378825fcc530cbba42f05311e
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