Sentence Similarity
sentence-transformers
PyTorch
mpnet
feature-extraction
text-embeddings-inference
Instructions to use AISE-TUDelft/java-pointer-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use AISE-TUDelft/java-pointer-classifier with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("AISE-TUDelft/java-pointer-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:
- 9e97bc43d1b4e30fe1535ea5b7b28dbef7f8547b535b8da3bd20416fd0bdd3d4
- Size of remote file:
- 6.99 kB
- SHA256:
- e18d0aba9bc3bb331e9fc05e824cfd6033b5902dfc71f8a16123ff9e32dafc36
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