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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- afe4f7fa5339cf053340327ec6bab280bb1a0f48ffc3490688899ac2ca81e13f
- Size of remote file:
- 293 MB
- SHA256:
- af3ff9029315194ca6daef97aa048898507bfdef842e9f6364268faf4bc9099a
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