sentence-transformers
ONNX
Safetensors
ColBERT
multi-vector
passage-retrieval
custom_code
🇪🇺 Region: EU
Instructions to use jinaai/jina-colbert-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use jinaai/jina-colbert-v2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("jinaai/jina-colbert-v2", trust_remote_code=True) sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
chore: add zh bm25 scores
Browse files
README.md
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| **pt** | 0.337 | 0.152 | 0.276 |
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| **ru** | 0.298 | 0.124 | 0.251 |
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| **vi** | 0.287 | 0.136 | 0.226 |
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| **zh** | 0.302 | 0.116 | 0.246 |
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