Instructions to use DDSC/roberta-base-scandinavian with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DDSC/roberta-base-scandinavian with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="DDSC/roberta-base-scandinavian")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("DDSC/roberta-base-scandinavian") model = AutoModelForMaskedLM.from_pretrained("DDSC/roberta-base-scandinavian", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from DDSC/roberta-base-scandinavian: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/DDSC/roberta-base-scandinavian/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://DDSC/roberta-base-scandinavian/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/DDSC/roberta-base-scandinavian/resolve/main/flax_model.msgpack
499 MB
- Xet hash:
- 16ca06386e4a36e94d20c8360bb946d9fb42a48f9b2d46ba93e5fb68c7772470
- Size of remote file:
- 499 MB
- SHA256:
- acf6202a6f4ccd700a240618d74f48f06463d9f52b74730452eb26f7547cd736
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