Instructions to use versae/roberta-base-ncc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use versae/roberta-base-ncc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="versae/roberta-base-ncc")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("versae/roberta-base-ncc") model = AutoModelForMaskedLM.from_pretrained("versae/roberta-base-ncc") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bab20d58280a3dde8db11e50a9c47817f6a8c1cc1d35ec8d8af5e88bea47013b
- Size of remote file:
- 499 MB
- SHA256:
- e6c1b729fa1c3dd64fbd625887667b363143278ab0161b5aeb411a6811b37680
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