Instructions to use macedonizer/mk-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use macedonizer/mk-roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="macedonizer/mk-roberta-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("macedonizer/mk-roberta-base") model = AutoModelForMaskedLM.from_pretrained("macedonizer/mk-roberta-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 58737b0fafcee95ff98ce58f740f528e6ccf779c86a42e10fd9f88fb101f5101
- Size of remote file:
- 2.29 kB
- SHA256:
- ef99a94cdac6dbe7a598d14bbe06802a17e3accbb209ee42d18bc203ee14ed55
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