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:
- a543e99eb5cbc45a862b4d4a1045a5f7cdaf9d544011cd521eac4ab2eb884fea
- Size of remote file:
- 334 MB
- SHA256:
- bd45fb7c86572b13179a28ec1739f30d427fdb30fd86c90e8f3a4c8f213485d7
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