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

microsoft
/
BiomedVLP-BioViL-T

Feature Extraction
Transformers
PyTorch
Safetensors
English
exbert
custom_code
Model card Files Files and versions
xet
Community
8

Instructions to use microsoft/BiomedVLP-BioViL-T with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use microsoft/BiomedVLP-BioViL-T with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="microsoft/BiomedVLP-BioViL-T", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("microsoft/BiomedVLP-BioViL-T", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
BiomedVLP-BioViL-T
13.8 kB
Ctrl+K
Ctrl+K
  • 6 contributors
History: 4 commits
ozanoktay's picture
ozanoktay
Update the readme -- Out of scope use cases.
2194015 over 3 years ago
  • .gitattributes
    1.48 kB
    initial commit over 3 years ago
  • README.md
    12.3 kB
    Update the readme -- Out of scope use cases. over 3 years ago