Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-small-dm2000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-small-dm2000 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-small-dm2000") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-small-dm2000") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 428378f80e78beeb239056a86137a138aaf7ff6a9ba706c3ab74dfbccc0b1fa4
- Size of remote file:
- 968 MB
- SHA256:
- de32ea74a9596534d4c628fa90bf8e5432c6c4da05bf6e8a3bf8a8216f98f99a
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