Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-tiny with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-tiny") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-tiny", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from google/t5-efficient-tiny: direct link, hf CLI and curl.
- Browser
- Download file 1.39 MB
-
https://huggingface.co/google/t5-efficient-tiny/resolve/main/tokenizer.json
- Command line
-
hf download hf://google/t5-efficient-tiny/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/google/t5-efficient-tiny/resolve/main/tokenizer.json
1.39 MB
File too large to display, you can check the raw version instead.