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

ayush1701
/
my-deberta

Feature Extraction
Transformers
google-tensorflow TensorFlow
deberta
generated_from_keras_callback
Model card Files Files and versions
xet
Community

Instructions to use ayush1701/my-deberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use ayush1701/my-deberta with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="ayush1701/my-deberta")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("ayush1701/my-deberta")
    model = AutoModel.from_pretrained("ayush1701/my-deberta")
  • Notebooks
  • Google Colab
  • Kaggle
my-deberta
555 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
ayush1701's picture
ayush1701
add model
950f581 almost 4 years ago
  • .gitattributes
    1.17 kB
    initial commit almost 4 years ago
  • README.md
    859 Bytes
    add model almost 4 years ago
  • config.json
    884 Bytes
    add model almost 4 years ago
  • tf_model.h5
    555 MB
    xet
    add model almost 4 years ago