Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-small-el48 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-small-el48 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-small-el48") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-small-el48", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from google/t5-efficient-small-el48: direct link, hf CLI and curl.
- Browser
- Download file 771 MB
-
https://huggingface.co/google/t5-efficient-small-el48/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://google/t5-efficient-small-el48/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/google/t5-efficient-small-el48/resolve/main/flax_model.msgpack
771 MB
- Xet hash:
- eb63714a1d787e89c73e048d816ad3632985ddbf275798bd31d2bf62d8c93dd2
- Size of remote file:
- 771 MB
- SHA256:
- 8b8aa39ba635646aea809aee7d739fdb3e319bd553a8da9bb723abcccadd9082
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