Hugging Face's logo Hugging Face
  • Models
  • Datasets
  • Spaces
  • Buckets new
  • Docs
  • Enterprise
  • Pricing

  • Log In
  • Sign Up

timm
/
vit_pe_spatial_tiny_patch16_512.fb

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

Instructions to use timm/vit_pe_spatial_tiny_patch16_512.fb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • timm

    How to use timm/vit_pe_spatial_tiny_patch16_512.fb with timm:

    import timm
    
    model = timm.create_model("hf_hub:timm/vit_pe_spatial_tiny_patch16_512.fb", pretrained=True)
  • Transformers

    How to use timm/vit_pe_spatial_tiny_patch16_512.fb with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-feature-extraction", model="timm/vit_pe_spatial_tiny_patch16_512.fb")
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("timm/vit_pe_spatial_tiny_patch16_512.fb", dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Model card for vit_pe_spatial_tiny_patch16_512.fb

Model card for vit_pe_spatial_tiny_patch16_512.fb

Downloads last month
90
Inference Providers NEW
Image Feature Extraction
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

Collection including timm/vit_pe_spatial_tiny_patch16_512.fb

Perception Encoder

Collection
OpenCLIP (PE Core image + text) and timm PE Core, Spatial, Lang (ViT only) weights. NOTE: These weights do not work with original modeling code. • 19 items • Updated Sep 19, 2025 • 7
Company
TOS Privacy About Careers
Website
Models Datasets Spaces Pricing Docs