Text Classification
sentence-transformers
Safetensors
setfit
English
multilingual
bert
persuasion
moderation
rhetoric
explainable-ai
trust
labse
timetotrust
text-embeddings-inference
Instructions to use jjprietotorres/labse-persuasion-detection-agnostic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use jjprietotorres/labse-persuasion-detection-agnostic with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("jjprietotorres/labse-persuasion-detection-agnostic") 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] - setfit
How to use jjprietotorres/labse-persuasion-detection-agnostic with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("jjprietotorres/labse-persuasion-detection-agnostic") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- da9eb3d6574ecbc9f24a2f8670297aad20e4c7ca40fccf4b2b6b7f1b9890707c
- Size of remote file:
- 31.6 kB
- SHA256:
- 1c8b99a6c9711f2908020a61775ef88d23c3cc447fe959c7d886e0d7c5929e46
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