Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-base-ff12000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-base-ff12000 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-base-ff12000") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-base-ff12000") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 33d3fc0f94db10d2a888c4dbef0257f4a5dd4acac684e731ec23f514e62b574f
- Size of remote file:
- 2.25 GB
- SHA256:
- 1fdebbb925200c943590b3b0c64acf61fa421d4158f410e94b0d28c92466cdfa
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