Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-base-kv128 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-base-kv128 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-base-kv128") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-base-kv128") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 13f8e85c81721abdc95dbfca4f73676905915271705d13c9ba19963f4a1e6047
- Size of remote file:
- 1.23 GB
- SHA256:
- 1b0676436127df2f003bbee16c3197010f95352aa8bc3cc5bd70e4dc0d69476f
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