Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-tiny-nl24 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-tiny-nl24 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-tiny-nl24") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-tiny-nl24", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from google/t5-efficient-tiny-nl24: direct link, hf CLI and curl.
- Browser
- Download file 209 MB
-
https://huggingface.co/google/t5-efficient-tiny-nl24/resolve/refs%2Fpr%2F1/flax_model.msgpack
- Command line
-
hf download hf://google/t5-efficient-tiny-nl24@refs/pr/1/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/google/t5-efficient-tiny-nl24/resolve/refs%2Fpr%2F1/flax_model.msgpack
209 MB
- Xet hash:
- 2f7432c4c8624cd79eb1c460e3c7518ee00abbdf312eee1d9a2dfdc98a825585
- Size of remote file:
- 209 MB
- SHA256:
- 0ec59520610fd1ca696bf9333710e8e9b939fe71719f908164a9b3db6596f575
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