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
Commit History
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Adding `safetensors` variant of this model
This is an automated PR created with https://huggingface.co/spaces/safetensors/convert This new file is equivalent to `pytorch_model.bin` but safe in the sense that no arbitrary code can be put into it. These files also happen to load much faster than their pytorch counterpart: https://colab.research.google.com/github/huggingface/notebooks/blob/main/safetensors_doc/en/speed.ipynb The widgets on your model page will run using this model even if this is not merged making sure the file actually works. If you find any issues: please report here: https://huggingface.co/spaces/safetensors/convert/discussions Feel free to ignore this PR.83ba10c
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Adding generation config file(s)
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Update README.md (#1)
- Update README.md (20c3bf27e4cd91bac3206b9acf95e36b6fc99156) Co-authored-by: Loïck BOURDOIS <lbourdois@users.noreply.huggingface.co>c40ca44
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Fix paper link
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upload flax model
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allow flax
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Update README.md
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Create README.md
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add tok
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upload all byt5-large files
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initial commit
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