Instructions to use formulae/reBERT-multilingual with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use formulae/reBERT-multilingual with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="formulae/reBERT-multilingual")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("formulae/reBERT-multilingual") model = AutoModelForMaskedLM.from_pretrained("formulae/reBERT-multilingual") - Notebooks
- Google Colab
- Kaggle
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README.md
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- XLM-RoBERTa base (multilingual)
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- BERT base cased (multilingual)
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## Custom merging technique to combine weights from both base models into one unified model
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# Mask token: <mask>
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- XLM-RoBERTa base (multilingual)
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- BERT base cased (multilingual)
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## Custom merging technique to combine weights from both base models into one unified model
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