Sentence Similarity
sentence-transformers
PyTorch
mpnet
feature-extraction
text-embeddings-inference
Instructions to use AISE-TUDelft/java-usage-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use AISE-TUDelft/java-usage-classifier with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("AISE-TUDelft/java-usage-classifier") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 65844ba3ce47cb4f480679ef4342b902aad6e3af2048ea2f6705e87c30f5a275
- Size of remote file:
- 438 MB
- SHA256:
- 7c7485e5814f08d3cee12cc753b566879206f4ce237264a093d230659ad8b613
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