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

  • Log In
  • Sign Up

Angad23
/
upar2027

timm
pedestrian-attribute-recognition
person-retrieval
upar
Model card Files Files and versions
xet
Community

Instructions to use Angad23/upar2027 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • timm

    How to use Angad23/upar2027 with timm:

    import timm
    
    model = timm.create_model("hf-hub:Angad23/upar2027", pretrained=True)
  • Notebooks
  • Google Colab
  • Kaggle
upar2027
1.82 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 9 commits
Angad23's picture
Angad23
Checksums for the three weight files
9910410 verified 8 days ago
  • .gitattributes
    1.52 kB
    initial commit 9 days ago
  • README.md
    1.37 kB
    Track 1 final entry is T1-d (79.55) 8 days ago
  • clipL_metaclip_ep4.pt
    606 MB
    xet
    Add trained weights 9 days ago
  • clipL_openai_ep4.pt
    606 MB
    xet
    Add trained weights 9 days ago
  • eva02L_lpft_ep6.pt
    607 MB
    xet
    Add trained weights 9 days ago
  • weights.sha256
    259 Bytes
    Checksums for the three weight files 8 days ago