Sentence Similarity
sentence-transformers
PyTorch
mpnet
feature-extraction
text-embeddings-inference
Instructions to use Watwat100/32data with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Watwat100/32data with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Watwat100/32data") 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:
- d9baa88c27bd7135461d4ad6b41845cbe90e882745adff1e1b406faae725cbe3
- Size of remote file:
- 7.12 kB
- SHA256:
- 9726f8a433a5ec7a149fa18240fb65ecc8b4576980c6d87f33a0e53d00e51f68
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