Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
dense
Generated from Trainer
loss:MultipleNegativesRankingLoss
text-embeddings-inference
Instructions to use kiel2/KielEmbed-Mini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use kiel2/KielEmbed-Mini with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("kiel2/KielEmbed-Mini") sentences = [ "Name a style of hot yoga.", "Bikram.", "Tallahassee is the capital of Florida", "I want a redhead woman with tattoos and big boobs and a big ass" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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