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leo-vnuuet
/
ColQwen3.5-2B-Embedding

Feature Extraction
PEFT
Safetensors
Transformers
ColPali
English
document-retrieval
multi-vector-embedding
matryoshka
Model card Files Files and versions
xet
Community

Instructions to use leo-vnuuet/ColQwen3.5-2B-Embedding with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • PEFT

    How to use leo-vnuuet/ColQwen3.5-2B-Embedding with PEFT:

    Task type is invalid.
  • Transformers

    How to use leo-vnuuet/ColQwen3.5-2B-Embedding with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="leo-vnuuet/ColQwen3.5-2B-Embedding")
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("leo-vnuuet/ColQwen3.5-2B-Embedding", dtype="auto")
  • ColPali

    How to use leo-vnuuet/ColQwen3.5-2B-Embedding with ColPali:

    # No code snippets available yet for this library.
    
    # To use this model, check the repository files and the library's documentation.
    
    # Want to help? PRs adding snippets are welcome at:
    # https://github.com/huggingface/huggingface.js
  • Notebooks
  • Google Colab
  • Kaggle
ColQwen3.5-2B-Embedding
135 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 4 commits
leo-vnuuet's picture
leo-vnuuet
Update README.md
38f3708 verified about 2 months ago
  • embedder
    update README, usage implementation 2 months ago
  • .gitattributes
    1.52 kB
    initial commit 2 months ago
  • README.md
    6.22 kB
    Update README.md about 2 months ago
  • adapter_config.json
    1.2 kB
    update README, usage implementation 2 months ago
  • adapter_model.safetensors
    135 MB
    xet
    update README, usage implementation 2 months ago