Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-large-el2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-large-el2 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-large-el2") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-large-el2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4718fd5e8c20c09e1202f1898903047e474f635038c5865b3fd8585275d842a0
- Size of remote file:
- 1.84 GB
- SHA256:
- a79303c6b80a7669d133282ac5269d10257ecd7cbc7c0ed8657cf8b9ec20d85e
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