Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-small-ff3000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-small-ff3000 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-small-ff3000") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-small-ff3000") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3a87fbb391301d842886037d671371a03609dbf1e4dccf971313ada40c93e6ca
- Size of remote file:
- 292 MB
- SHA256:
- 3010c20a3f6f0644937233cd8da229d97398c96e057e21db36df405d5758b3d5
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