Instructions to use Davlan/oyo-bert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Davlan/oyo-bert-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Davlan/oyo-bert-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Davlan/oyo-bert-base") model = AutoModelForMaskedLM.from_pretrained("Davlan/oyo-bert-base") - Notebooks
- Google Colab
- Kaggle
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### Acknowledgment
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We thank @stefan-it for providing the pre-processing and pre-training scripts. Finally, we would like to thank Google Cloud for providing us access to TPU v3-8 through the free cloud credits. Model trained using flax, before converted to pytorch.
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### BibTeX entry and citation info.
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### Acknowledgment
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We thank [@stefan-it](https://github.com/stefan-it) for providing the pre-processing and pre-training scripts. Finally, we would like to thank Google Cloud for providing us access to TPU v3-8 through the free cloud credits. Model trained using flax, before converted to pytorch.
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### BibTeX entry and citation info.
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