Instructions to use palat/bort with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use palat/bort with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("palat/bort") model = AutoModelForSeq2SeqLM.from_pretrained("palat/bort") - Notebooks
- Google Colab
- Kaggle
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BORT is a pretrained LLM that is designed to accept a mixture of English phonemes (in IPA) and orthography, made with clinical language evaluation tasks in mind. From the paper:
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## Acknowledgements
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BORT is a pretrained LLM that is designed to accept a mixture of English phonemes (in IPA) and orthography, made with clinical language evaluation tasks in mind. From the paper:
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Robert Gale, Alexandra C. Salem, Gerasimos Fergadiotis, and Steven Bedrick. 2023. [**Mixed Orthographic/Phonemic Language Modeling: Beyond Orthographically Restricted Transformers (BORT).**](https://robertcgale.com/pub/2023-acl-bort-paper.pdf) In Proceedings of the 8th Workshop on Representation Learning for NLP (RepL4NLP-2023), pages TBD, Online. Association for Computational Linguistics. [[paper]](https://robertcgale.com/pub/2023-acl-bort-paper.pdf) [[poster]](https://robertcgale.com/pub/2023-acl-bort-poster.pdf)
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## Acknowledgements
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