Instructions to use macedonizer/ba-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use macedonizer/ba-roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="macedonizer/ba-roberta-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("macedonizer/ba-roberta-base") model = AutoModelForMaskedLM.from_pretrained("macedonizer/ba-roberta-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Stojanco Tudzarski commited on
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README.md fixed
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Pretrained model on Bosnian language using a masked language modeling (MLM) objective. It was introduced in this paper and first released in this repository. This model is case-sensitive: it makes a difference between sarajevo and Sarajevo.
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# Model description
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# BA-RoBERTa base model
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Pretrained model on Bosnian language using a masked language modeling (MLM) objective. It was introduced in this paper and first released in this repository. This model is case-sensitive: it makes a difference between sarajevo and Sarajevo.
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# Model description
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