Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-large-dm2000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-large-dm2000 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-large-dm2000") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-large-dm2000") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f2259144438a49d549dbb8093d5592ed697d2ac0576fe529fa9cd96f7774e2dd
- Size of remote file:
- 5.9 GB
- SHA256:
- d16c0162396647013ec2194828b254723531ef819d6370ff21ce5d57a96ca5ea
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