Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-large-nh32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-large-nh32 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-large-nh32") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-large-nh32") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3da967ace0efc06d71ff871b5d31e9310956e6f69741092813fd4d12be46b7ef
- Size of remote file:
- 4.16 GB
- SHA256:
- a6cb70d9a18b7b3be015eb0ba0e73d0c03dc9763cb1bc4aeecdb3c5e8f584750
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