Sentence Similarity
sentence-transformers
ONNX
Safetensors
feature-extraction
Generated from Trainer
dataset_size:62698210
loss:MatryoshkaLoss
loss:MultipleNegativesRankingLoss
Eval Results
Instructions to use sentence-transformers/static-similarity-mrl-multilingual-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use sentence-transformers/static-similarity-mrl-multilingual-v1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("sentence-transformers/static-similarity-mrl-multilingual-v1") sentences = [ "A man is jumping unto his filthy bed.", "A man is ouside near the beach.", "The bed is dirty.", "The man is on the moon." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 14b66a06e908dde7a035c6a4368cdf064202ca3243f749b639c56498081d9365
- Size of remote file:
- 434 MB
- SHA256:
- 8245ab78ee71dded845a82d2270fcb9e785b29dad0e1619f69d5390c47d9ba00
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