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")# pip install -U transformers accelerate # 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
Download pytorch_model.bin from DDSC/roberta-base-danish: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/DDSC/roberta-base-danish/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://DDSC/roberta-base-danish/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/DDSC/roberta-base-danish/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- a483721bc0e9b675fb1c9ff621b39ce0bd16e3f2031de88ed5d66a3cc94a5f30
- Size of remote file:
- 499 MB
- SHA256:
- 0efc1a11b846b3fea6941d9948040f06c5d9c7fa3b5a38e18d23040628797f77
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