Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
Generated from Trainer
dataset_size:867042
loss:MultipleNegativesRankingLoss
text-embeddings-inference
Instructions to use agentlans/multilingual-e5-small-aligned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use agentlans/multilingual-e5-small-aligned with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("agentlans/multilingual-e5-small-aligned") sentences = [ "An air strike.", "מר פרקינסון היה מזועזע אם היה יודע איך מר פוקס מתנהג.", "Sonia: Jangan berkata begitu.", "En luftattack." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 11948091ec8436a1dcf4bc836529ad16dc7bb56ef60a05fa1fa3e429dc5afa67
- Size of remote file:
- 471 MB
- SHA256:
- 942c83794ae8938f752c87d72664976ea2b516bf0c9532f89c51e2cc1f08a9d3
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