Transformers
PyTorch
TensorFlow
JAX
English
t5
text2text-generation
deep-narrow
text-generation-inference
Instructions to use google/t5-efficient-xl-nl28 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/t5-efficient-xl-nl28 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/t5-efficient-xl-nl28") model = AutoModelForSeq2SeqLM.from_pretrained("google/t5-efficient-xl-nl28", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from google/t5-efficient-xl-nl28: direct link, hf CLI and curl.
- Browser
- Download file 13.3 GB
-
https://huggingface.co/google/t5-efficient-xl-nl28/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://google/t5-efficient-xl-nl28/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/google/t5-efficient-xl-nl28/resolve/main/flax_model.msgpack
13.3 GB
- Xet hash:
- 6fdbf49a19c0a73c92c09a22128e3fdbe54932aa8de3486aa3857aa615643478
- Size of remote file:
- 13.3 GB
- SHA256:
- d19f624eb75d1b5d112c88d97baf5739d2fc659a74278c25726d08f847be354f
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