Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-large-dl32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-large-dl32 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-large-dl32") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-large-dl32") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ef78fdd377b639cbd2a999f6b38d6eda8c10237246eaa20d630cb2cc335c8f67
- Size of remote file:
- 3.49 GB
- SHA256:
- 36774cf47ec217205fb51a6149d6b2f4b3c064cf9f34014af76ddfb6e897f976
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