Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-xl-nl2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-xl-nl2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-xl-nl2") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-xl-nl2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from google/t5-efficient-xl-nl2: direct link, hf CLI and curl.
- Browser
- Download file 1.07 GB
-
https://huggingface.co/google/t5-efficient-xl-nl2/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://google/t5-efficient-xl-nl2/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/google/t5-efficient-xl-nl2/resolve/main/flax_model.msgpack
1.07 GB
- Xet hash:
- fa2dc93097047ed3bebbf1e191c7acbcd16d9f34ddb17b7d45258b081b94975e
- Size of remote file:
- 1.07 GB
- SHA256:
- a62af7d22b50d33033a032c4fa8da40dac9231f25dc792982c17cadcdea0faa9
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