Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-base-ff9000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-base-ff9000 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-base-ff9000") model = AutoModelForMultimodalLM.from_pretrained("google/t5-efficient-base-ff9000") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8eb64748e4b21d883c14cabffabe42de592d2603172129c3ad799ef89179b37c
- Size of remote file:
- 1.8 GB
- SHA256:
- 525f4c7b9ac199a4ace783276156c9cf6ef19f259211cc7608ae344e8ba15473
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