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woooooz
/
WeMM-Embedding-9B

Feature Extraction
Transformers
Safetensors
qwen3_5
image-text-to-text
multimodal-embedding
retrieval
evaluation
custom_code
Model card Files Files and versions
xet
Community

Instructions to use woooooz/WeMM-Embedding-9B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use woooooz/WeMM-Embedding-9B with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="woooooz/WeMM-Embedding-9B", trust_remote_code=True)
    # pip install -U transformers accelerate
    # Load model directly
    from transformers import AutoProcessor, AutoModelForMultimodalLM
    
    processor = AutoProcessor.from_pretrained("woooooz/WeMM-Embedding-9B", trust_remote_code=True)
    model = AutoModelForMultimodalLM.from_pretrained("woooooz/WeMM-Embedding-9B", trust_remote_code=True, device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
WeMM-Embedding-9B / evaluation /vendor
45.9 MB
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  • 1 contributor
History: 1 commit
woooooz's picture
woooooz
Package upstream model with reproducible local MMEB evaluation
bb2b5cc verified 7 days ago
  • transformers-5.6.0.dev0.dist-info
    Package upstream model with reproducible local MMEB evaluation 7 days ago
  • transformers
    Package upstream model with reproducible local MMEB evaluation 7 days ago