Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-tiny-ff12000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-tiny-ff12000 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-tiny-ff12000") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-tiny-ff12000", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f942a5b2c4b366d6c36a040dd8ed1e24322447d1411c78be0094f3a4b426ef40
- Size of remote file:
- 247 MB
- SHA256:
- 658b36260b74199a44a4c5d51788eae2cb1ced1ae1bf14e83f9d45e7762c06ed
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