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:
- 42b590d4ead7bc9df31f42774acdda0c772653cb4f122d3b38e93ad24de53c55
- Size of remote file:
- 623 Bytes
- SHA256:
- c30834c9eacd278233301e5743cc24659976bc3e5f25f5b70bde06c4f27d0334
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