Hugging Face's logo Hugging Face
  • Models
  • Datasets
  • Spaces
  • Buckets new
  • Docs
  • Enterprise
  • Pricing
    • Website
      • Tasks
      • HuggingChat
      • Collections
      • Languages
      • Organizations
    • Community
      • Blog
      • Posts
      • Daily Papers
      • Learn
      • Discord
      • Forum
      • GitHub
    • Solutions
      • Team & Enterprise
      • Hugging Face PRO
      • Enterprise Support
      • Inference Providers
      • Inference Endpoints
      • Storage Buckets

  • Log In
  • Sign Up

p1atdev
/
siglip2-base-patch16-384-vision

Image Feature Extraction
Transformers
Safetensors
siglip_vision_model
Model card Files Files and versions
xet
Community

Instructions to use p1atdev/siglip2-base-patch16-384-vision with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use p1atdev/siglip2-base-patch16-384-vision with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-feature-extraction", model="p1atdev/siglip2-base-patch16-384-vision")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("p1atdev/siglip2-base-patch16-384-vision")
    model = AutoModel.from_pretrained("p1atdev/siglip2-base-patch16-384-vision")
  • Notebooks
  • Google Colab
  • Kaggle
siglip2-base-patch16-384-vision
373 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
p1atdev's picture
p1atdev
Update README.md
c82cf8e verified about 1 year ago
  • .gitattributes
    1.52 kB
    initial commit about 1 year ago
  • README.md
    213 Bytes
    Update README.md about 1 year ago
  • config.json
    417 Bytes
    Upload model about 1 year ago
  • model.safetensors
    373 MB
    xet
    Upload model about 1 year ago