Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-mini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-mini with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-mini") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-mini", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from google/t5-efficient-mini: direct link, hf CLI and curl.
- Browser
- Download file 125 MB
-
https://huggingface.co/google/t5-efficient-mini/resolve/refs%2Fpr%2F1/flax_model.msgpack
- Command line
-
hf download hf://google/t5-efficient-mini@refs/pr/1/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/google/t5-efficient-mini/resolve/refs%2Fpr%2F1/flax_model.msgpack
125 MB
- Xet hash:
- 8d2f7e9a4c385e812890d11262bb55572573d0f50ae5aeff96c4033b9ecd22f7
- Size of remote file:
- 125 MB
- SHA256:
- 5ef3e1d0188a86571d2dfc6b0f4abeadbe1d279a1ce40a6bc032a244021e9249
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