Instructions to use macedonizer/sr-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use macedonizer/sr-roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="macedonizer/sr-roberta-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("macedonizer/sr-roberta-base") model = AutoModelForMaskedLM.from_pretrained("macedonizer/sr-roberta-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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language:
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- sr
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thumbnail: https://huggingface.co/macedonizer/sr-roberta-base/lets-talk-about-nlp-sr.jpg
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tags:
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- masked-lm
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license:
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datasets:
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- wiki-sr
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language:
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- sr
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thumbnail: https://huggingface.co/macedonizer/sr-roberta-base/lets-talk-about-nlp-sr.jpg
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tags:
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- masked-lm
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license: apache-2.0
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datasets:
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- wiki-sr
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