Instructions to use dsfsi/PuoBERTa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dsfsi/PuoBERTa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="dsfsi/PuoBERTa")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("dsfsi/PuoBERTa") model = AutoModelForMaskedLM.from_pretrained("dsfsi/PuoBERTa") - Notebooks
- Google Colab
- Kaggle
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README.md
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title = {PuoBERTa: Training and evaluation of a curated language model for Setswana},
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author = {Vukosi Marivate and Moseli Mots'Oehli and Valencia Wagner and Richard Lastrucci and Isheanesu Dzingirai},
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year = {2023},
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booktitle= {SACAIR 2023
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keywords = {NLP},
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preprint_url = {https://arxiv.org/abs/2310.09141},
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dataset_url = {https://github.com/dsfsi/PuoBERTa},
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title = {PuoBERTa: Training and evaluation of a curated language model for Setswana},
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author = {Vukosi Marivate and Moseli Mots'Oehli and Valencia Wagner and Richard Lastrucci and Isheanesu Dzingirai},
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year = {2023},
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booktitle= {Artificial Intelligence Research. SACAIR 2023. Communications in Computer and Information Science},
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url= {https://link.springer.com/chapter/10.1007/978-3-031-49002-6_17},
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keywords = {NLP},
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preprint_url = {https://arxiv.org/abs/2310.09141},
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dataset_url = {https://github.com/dsfsi/PuoBERTa},
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