Sentence Similarity
sentence-transformers
Safetensors
modernbert
visual-document-retrieval
document-ai
colnanovdr
nanovdr
late-interaction
multi-vector
knowledge-distillation
text-embeddings-inference
Instructions to use nanovdr/ColNanoVDR-Q-Ettin400M-ColQwen35-320-ML with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use nanovdr/ColNanoVDR-Q-Ettin400M-ColQwen35-320-ML with sentence-transformers:
from sentence_transformers import MultiVectorEncoder model = MultiVectorEncoder("nanovdr/ColNanoVDR-Q-Ettin400M-ColQwen35-320-ML") 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
Welcome to the community
The community tab is the place to discuss and collaborate with the HF community!