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DAMO-NLP-SG
/
VL3-SigLIP-NaViT

Image Feature Extraction
Transformers
Safetensors
English
videollama3_vision_encoder
feature-extraction
visual-encoder
multi-modal-large-language-model
custom_code
Model card Files Files and versions
xet
Community
7

Instructions to use DAMO-NLP-SG/VL3-SigLIP-NaViT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use DAMO-NLP-SG/VL3-SigLIP-NaViT with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-feature-extraction", model="DAMO-NLP-SG/VL3-SigLIP-NaViT", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("DAMO-NLP-SG/VL3-SigLIP-NaViT", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
New discussion
Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

Update image_processing_videollama3.py

1
#7 opened 8 months ago by
seungeon-enerzai

Does this only supports image?

➕ 1
#6 opened about 1 year ago by
2U1

what is the difference between this model and "DAMO-NLP-SG/SigLIP-NaViT"?

1
#5 opened about 1 year ago by
hao98

How to encode batch picture

#4 opened over 1 year ago by
kurisu0306

Add model card metadata

#3 opened over 1 year ago by
nielsr

Training details

#2 opened over 1 year ago by
lucasjin

Rotary embedding why using 1d rather than 2d?

#1 opened over 1 year ago by
lucasjin
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