Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-xl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-xl with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-xl") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-xl", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from google/t5-efficient-xl: direct link, hf CLI and curl.
- Browser
- Download file 11.4 GB
-
https://huggingface.co/google/t5-efficient-xl/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://google/t5-efficient-xl/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/google/t5-efficient-xl/resolve/main/flax_model.msgpack
11.4 GB
- Xet hash:
- 33ace474ff8cc9b4039a1165fa46ee90c3c6b3f72fa392cbc8d610d99a99ea28
- Size of remote file:
- 11.4 GB
- SHA256:
- 43f35656c7bd042bfd62740c6eb0b5c1703f38a4b20007d5fb6fbecd5d51f6cc
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