Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-base-nl4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-base-nl4 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-base-nl4") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-base-nl4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from google/t5-efficient-base-nl4: direct link, hf CLI and curl.
- Browser
- Download file 363 MB
-
https://huggingface.co/google/t5-efficient-base-nl4/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://google/t5-efficient-base-nl4/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/google/t5-efficient-base-nl4/resolve/main/flax_model.msgpack
363 MB
- Xet hash:
- 071ecf8c469f382d42f9a788a4dfbb7563af049c3ba0dfc530de30e8325c15b1
- Size of remote file:
- 363 MB
- SHA256:
- ef9d87db19aa6398c4a2f44bbfc77c1163e29ee8b57ad1b08e8d0e6ed8e8d5f2
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