Sentence Similarity
sentence-transformers
Safetensors
German
modernbert_hash_moe_hybrid
ColBERT
late-interaction
multi-vector
mixture-of-experts
moedernbert
retrieval
legal
german
custom_code
Instructions to use VAGOsolutions/SauerkrautLM-MoEdernColBERT-1.5M-Legal-DE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use VAGOsolutions/SauerkrautLM-MoEdernColBERT-1.5M-Legal-DE with sentence-transformers:
from sentence_transformers import MultiVectorEncoder model = MultiVectorEncoder("VAGOsolutions/SauerkrautLM-MoEdernColBERT-1.5M-Legal-DE", trust_remote_code=True) queries = ["Which planet is known as the Red Planet?"] documents = [ "Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", ] query_embeddings = model.encode_query(queries) document_embeddings = model.encode_document(documents) similarities = model.similarity(query_embeddings, document_embeddings) print(similarities) - Notebooks
- Google Colab
- Kaggle
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