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illuin-conteb
/
modern-colbert-insent

Feature Extraction
sentence-transformers
Safetensors
modernbert
ColBERT
PyLate
contextual-embeddings
sentence-similarity
Generated from Trainer
text-embeddings-inference
Model card Files Files and versions
xet
Community
1

Instructions to use illuin-conteb/modern-colbert-insent with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use illuin-conteb/modern-colbert-insent 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="illuin-conteb/modern-colbert-insent")
    
    queries_emb = model.encode(queries, is_query=True)
    docs_emb = model.encode(documents, is_query=False)
  • Notebooks
  • Google Colab
  • Kaggle
modern-colbert-insent
3 GB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 5 commits
manu's picture
manu
Update README.md
0c5c10f verified 12 months ago
  • 1_Dense
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  • .gitattributes
    1.52 kB
    initial commit 12 months ago
  • README.md
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  • config.json
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  • config_sentence_transformers.json
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  • model.safetensors
    298 MB
    xet
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  • modules.json
    216 Bytes
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  • sentence_bert_config.json
    54 Bytes
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  • special_tokens_map.json
    581 Bytes
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  • tokenizer.json
    3.58 MB
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  • tokenizer_config.json
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  • training_config.yml
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