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
feat: revert the mask padding default setting
Browse files- artifact.metadata +1 -1
artifact.metadata
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@@ -27,7 +27,7 @@
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"ignore_scores": true,
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"model_name": "jinaai/jina-colbert-v2",
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"query_maxlen": 32,
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"attend_to_mask_tokens":
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"interaction": "colbert",
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"doc_maxlen": 300,
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"mask_punctuation": true,
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"ignore_scores": true,
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"model_name": "jinaai/jina-colbert-v2",
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"query_maxlen": 32,
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"attend_to_mask_tokens": true,
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"interaction": "colbert",
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"doc_maxlen": 300,
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"mask_punctuation": true,
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