Sentence Similarity
sentence-transformers
PyTorch
mpnet
feature-extraction
text-embeddings-inference
Instructions to use AISE-TUDelft/pharo-example-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use AISE-TUDelft/pharo-example-classifier with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("AISE-TUDelft/pharo-example-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:
- 198a5a827851ae3471d32b494e1ff1224bc236378c1cf896390a438d96764aad
- Size of remote file:
- 438 MB
- SHA256:
- 1bb17b103685ac6ee2a1faf67cd1a506cfd6a481a9b3ecc41c907e0f9286f670
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