Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-tiny-nl16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-tiny-nl16 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-tiny-nl16") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-tiny-nl16", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from google/t5-efficient-tiny-nl16: direct link, hf CLI and curl.
- Browser
- Download file 150 MB
-
https://huggingface.co/google/t5-efficient-tiny-nl16/resolve/refs%2Fpr%2F1/flax_model.msgpack
- Command line
-
hf download hf://google/t5-efficient-tiny-nl16@refs/pr/1/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/google/t5-efficient-tiny-nl16/resolve/refs%2Fpr%2F1/flax_model.msgpack
150 MB
- Xet hash:
- 221c64cc8ec681fe48dee4f3c1b0a02927c7612fe5930dd74b578f470adc9ae4
- Size of remote file:
- 150 MB
- SHA256:
- 7ddc72ccf9c60ed0b4289a11d4eda9ad79bb9b25a8b17a25264240059396400f
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