Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-base-kv16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-base-kv16 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-base-kv16") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-base-kv16") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d9f627ecc65761180066709766f5363247c31b8878134cc5e64b2bc526c136d9
- Size of remote file:
- 637 MB
- SHA256:
- 5e2481919ed6dccc398dbd4139f3ad6f4ff791fe327a3434231f2f3e35dbce92
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