Sentence Similarity
sentence-transformers
PyTorch
English
mpnet
feature-extraction
text-embeddings-inference
Instructions to use flax-sentence-embeddings/all_datasets_v3_mpnet-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use flax-sentence-embeddings/all_datasets_v3_mpnet-base with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("flax-sentence-embeddings/all_datasets_v3_mpnet-base") 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:
- d7d9d77f0d9cb39d40cff40b4f9da2a00b25a7f0c8500ab6273105bb249ddfd1
- Size of remote file:
- 438 MB
- SHA256:
- 879a1f3543bda9609f8ae74c68236cc5049769fcac6fbd68a70aafd6762dca01
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