Text Classification
setfit
Safetensors
sentence-transformers
Danish
Few-Shot
Transformers
Text-classification
generated_from_setfit_traine
Computational_humanities
SSH
Social-work
Instructions to use CALDISS-AAU/da-reported-speech-e5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use CALDISS-AAU/da-reported-speech-e5 with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("CALDISS-AAU/da-reported-speech-e5") - sentence-transformers
How to use CALDISS-AAU/da-reported-speech-e5 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("CALDISS-AAU/da-reported-speech-e5") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5f077be07abb91ed75b6146001ac8d3218def78d7e8d75e493f696b022c227c5
- Size of remote file:
- 17.1 MB
- SHA256:
- f1cc44ad7faaeec47241864835473fd5403f2da94673f3f764a77ebcb0a803ec
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