Instructions to use google/byt5-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/byt5-base with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/byt5-base") model = AutoModelForSeq2SeqLM.from_pretrained("google/byt5-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from google/byt5-base: direct link, hf CLI and curl.
- Browser
- Download file 2.33 GB
-
https://huggingface.co/google/byt5-base/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://google/byt5-base/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/google/byt5-base/resolve/main/flax_model.msgpack
2.33 GB
- Xet hash:
- bfd0b5551d7fd8cecb9f3791af74ae2d2105be84885f02b8697ffc2caea77109
- Size of remote file:
- 2.33 GB
- SHA256:
- 629950458338aea8f00cd3969d2d4439d611891d9e3e33d7815d3ede347ffc26
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