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MBZUAI
/
Omni-Embed-Mini-0.9B

Feature Extraction
Transformers
Safetensors
English
omni_embed
embeddings
multimodal
omni-modal
retrieval
sentence-similarity
audio
speech
image
video
visual-document-retrieval
matryoshka
custom_code
Model card Files Files and versions
xet
Community

Instructions to use MBZUAI/Omni-Embed-Mini-0.9B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use MBZUAI/Omni-Embed-Mini-0.9B with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="MBZUAI/Omni-Embed-Mini-0.9B", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("MBZUAI/Omni-Embed-Mini-0.9B", trust_remote_code=True, device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle

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Preview of files found in this repository
  • backbone
    v1: paper release 8 days ago
  • .gitattributes
    1.57 kB
    v1: paper release 8 days ago
  • README.md
    5.79 kB
    v1: paper release 8 days ago
  • chat_template.jinja
    4.12 kB
    v1: paper release 8 days ago
  • config.json
    726 Bytes
    v1: paper release 8 days ago
  • configuration_omni_embed.py
    1.24 kB
    v1: paper release 8 days ago
  • dasheng_encoder.pt
    342 MB
    xet
    v1: paper release 8 days ago
  • modeling_omni_embed.py
    39.8 kB
    v1: paper release 8 days ago
  • processing_omni_embed.py
    25 kB
    fix loading from repo id 8 days ago
  • processor_config.json
    398 Bytes
    v1: paper release 8 days ago
  • projector_weights.pt
    261 MB
    xet
    v1: paper release 8 days ago
  • tokenizer.json
    11.4 MB
    xet
    v1: paper release 8 days ago
  • tokenizer_config.json
    576 Bytes
    v1: paper release 8 days ago
  • vision_encoder.pt
    201 MB
    xet
    v1: paper release 8 days ago
  • whisper_encoder.pt
    353 MB
    xet
    v1: paper release 8 days ago