Instructions to use google/byt5-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/byt5-large with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/byt5-large") model = AutoModelForSeq2SeqLM.from_pretrained("google/byt5-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from google/byt5-large: direct link, hf CLI and curl.
- Browser
- Download file 4.91 GB
-
https://huggingface.co/google/byt5-large/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://google/byt5-large/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/google/byt5-large/resolve/main/flax_model.msgpack
4.91 GB
- Xet hash:
- 182b71999fa70de6a80b8e879f4b0fbd80c9988036dbc02736069d00a8273def
- Size of remote file:
- 4.91 GB
- SHA256:
- 81bed393457b7340976e58d139b9355aa63edf4cef1e32dd3d89655918d1f990
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