Instructions to use CALDISS-AAU/DA-BERT_Old_News_V3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CALDISS-AAU/DA-BERT_Old_News_V3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="CALDISS-AAU/DA-BERT_Old_News_V3")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("CALDISS-AAU/DA-BERT_Old_News_V3") model = AutoModelForMaskedLM.from_pretrained("CALDISS-AAU/DA-BERT_Old_News_V3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from CALDISS-AAU/DA-BERT_Old_News_V3: direct link, hf CLI and curl.
- Browser
- Download file 498 MB
-
https://huggingface.co/CALDISS-AAU/DA-BERT_Old_News_V3/resolve/main/model.safetensors
- Command line
-
hf download hf://CALDISS-AAU/DA-BERT_Old_News_V3/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/CALDISS-AAU/DA-BERT_Old_News_V3/resolve/main/model.safetensors
498 MB
- Xet hash:
- af223d9f15beea8a00da609eda5a327cca427c2a3be209b8c3d678a9dda0952f
- Size of remote file:
- 498 MB
- SHA256:
- 4fe22288fdee4731bae237d5f10f276caf41ca34cdd8ade1c2b95d6219713c39
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