Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-small-nl32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-small-nl32 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-small-nl32") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-small-nl32", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from google/t5-efficient-small-nl32: direct link, hf CLI and curl.
- Browser
- Download file 1.01 GB
-
https://huggingface.co/google/t5-efficient-small-nl32/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://google/t5-efficient-small-nl32/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/google/t5-efficient-small-nl32/resolve/main/flax_model.msgpack
1.01 GB
- Xet hash:
- c230a34851d9987d93cf3fb0e56cfe6005b0b25855339303a16587dd27f31ea6
- Size of remote file:
- 1.01 GB
- SHA256:
- 731a304be4776255d7d43343a570e669041fea0a40f3c4f509f56ff50753d09f
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