Instructions to use DDSC/roberta-base-danish with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DDSC/roberta-base-danish with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="DDSC/roberta-base-danish")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("DDSC/roberta-base-danish") model = AutoModelForMaskedLM.from_pretrained("DDSC/roberta-base-danish", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a483721bc0e9b675fb1c9ff621b39ce0bd16e3f2031de88ed5d66a3cc94a5f30
- Size of remote file:
- 499 MB
- SHA256:
- 0efc1a11b846b3fea6941d9948040f06c5d9c7fa3b5a38e18d23040628797f77
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