Sentence Similarity
Safetensors
sentence-transformers
PyLate
eurobert
ColBERT
multi-vector
feature-extraction
multilingual
late-interaction
retrieval
pretrained
loss:Distillation
custom_code
Instructions to use VAGOsolutions/SauerkrautLM-EuroColBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use VAGOsolutions/SauerkrautLM-EuroColBERT with sentence-transformers:
from pylate import models queries = [ "Which planet is known as the Red Planet?", "What is the largest planet in our solar system?", ] documents = [ ["Mars is the Red Planet.", "Venus is Earth's twin."], ["Jupiter is the largest planet.", "Saturn has rings."], ] model = models.ColBERT(model_name_or_path="VAGOsolutions/SauerkrautLM-EuroColBERT") queries_emb = model.encode(queries, is_query=True) docs_emb = model.encode(documents, is_query=False) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3d7274b28ed6a73b45e3961ccf11dbac94412021a1e902f05a77618e7bd43f25
- Size of remote file:
- 17.2 MB
- SHA256:
- ac002ea0ba9357c0a350d19ead43584bbaf8f8eb40652a0c77111b15c6638ca4
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