Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-tiny-nh16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-tiny-nh16 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-tiny-nh16") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-tiny-nh16", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 74a4168927bde66456153de7ff5d81b66594ba75a28a6776197ef0267ef8074b
- Size of remote file:
- 100 MB
- SHA256:
- e09ffa003922c0085d13e5e29c95230ac40d25ff240988bf35c559da1d02f17f
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