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:
- 33f2429d80e78c1c3698e29b06b8666de34c7092aba731fe5566b3cc68c5e518
- Size of remote file:
- 637 MB
- SHA256:
- a870d465653a0af43716ac457fd140c3506d7f64b0ad6d5504e90b317beb735f
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