Sentence Similarity
sentence-transformers
Safetensors
German
ministral3
feature-extraction
retrieval
public-procurement
sustainability
Instructions to use IntelliProcure/TENDRIL-most-embed-de with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use IntelliProcure/TENDRIL-most-embed-de with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("IntelliProcure/TENDRIL-most-embed-de") sentences = [ "Das ist eine glückliche Person", "Das ist ein glücklicher Hund", "Das ist eine sehr glückliche Person", "Heute ist ein sonniger Tag" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
File size: 133 Bytes
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