Text Classification
sentence-transformers
Safetensors
English
questionnaire-harmonization
prototype-learning
impulse-control
Instructions to use julia-pfarr/HarmoniCA_impulse-control with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use julia-pfarr/HarmoniCA_impulse-control with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("julia-pfarr/HarmoniCA_impulse-control") 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:
- cdcbc22cffa94d0de7cb818e9e593c4eb1c146b2a894677dec10444ad43e8a42
- Size of remote file:
- 37.9 kB
- SHA256:
- f3d5c082b3b88144d02280f1eb6fe7ef944635ca6933cfb6cc3e1793656d2e43
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