Text Classification
Transformers
PyTorch
Danish
bert
danish
sentiment
Maltehb/danish-bert-botxo
Helsinki-NLP/opus-mt-en-da
go-emotion
Certainly
text-embeddings-inference
Instructions to use RJuro/Da-HyggeBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RJuro/Da-HyggeBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="RJuro/Da-HyggeBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("RJuro/Da-HyggeBERT") model = AutoModelForSequenceClassification.from_pretrained("RJuro/Da-HyggeBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from RJuro/Da-HyggeBERT: direct link, hf CLI and curl.
- Browser
- Download file 443 MB
-
https://huggingface.co/RJuro/Da-HyggeBERT/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://RJuro/Da-HyggeBERT/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/RJuro/Da-HyggeBERT/resolve/main/pytorch_model.bin
443 MB
- Xet hash:
- eeae389d65d5292d096d8554cf3606845cdbf920bfff7b14011533abbd9477dc
- Size of remote file:
- 443 MB
- SHA256:
- 1bfe554c51310b24a21f02b79f5870a6f3d601f585a460263dcd0199804eb7e8
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