Instructions to use aseifert/byt5-base-jfleg-wi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aseifert/byt5-base-jfleg-wi with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("aseifert/byt5-base-jfleg-wi") model = AutoModelForSeq2SeqLM.from_pretrained("aseifert/byt5-base-jfleg-wi", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 79520bce9725ae746a681aec6166dfacfbc6b6d9955df09dcbd411631df39fbc
- Size of remote file:
- 2.33 GB
- SHA256:
- 4c108e6a7fababe77f369094ce4fe8937988ea4eb2c48eeab6919aba6e94507a
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