Sentence Similarity
sentence-transformers
PyTorch
Safetensors
English
French
mpnet
feature-extraction
text-embeddings-inference
Instructions to use raphaelsty/semanlink_all_mpnet_base_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use raphaelsty/semanlink_all_mpnet_base_v2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("raphaelsty/semanlink_all_mpnet_base_v2") 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:
- 41968b7f94156e8db79b4a9468a0fb22cea279267b393d511df2c28e4fda9848
- Size of remote file:
- 438 MB
- SHA256:
- 7e6c28fd47455d2ca53d017b1274ef80d07f25bb0bfc16ac3082bd984df98222
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