Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-small-nl4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-small-nl4 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-small-nl4") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-small-nl4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from google/t5-efficient-small-nl4: direct link, hf CLI and curl.
- Browser
- Download file 183 MB
-
https://huggingface.co/google/t5-efficient-small-nl4/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://google/t5-efficient-small-nl4/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/google/t5-efficient-small-nl4/resolve/main/flax_model.msgpack
183 MB
- Xet hash:
- 94595c3f84246c17152776b9d4f9321081306911dfb15dff52892772db3b991c
- Size of remote file:
- 183 MB
- SHA256:
- 434be48652a745ef683fcc27321fa55cb01700026624049b40bb4d32c325dfea
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