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martingrzzler
/
clip-word-concreteness

Text Classification
Transformers
PyTorch
English
clip_text_model
psycholinguistic
word concreteness
Model card Files Files and versions
xet
Community
2

Instructions to use martingrzzler/clip-word-concreteness with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use martingrzzler/clip-word-concreteness with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="martingrzzler/clip-word-concreteness")
    # Load model directly
    from transformers import AutoTokenizer, CLIPForRegression
    
    tokenizer = AutoTokenizer.from_pretrained("martingrzzler/clip-word-concreteness")
    model = CLIPForRegression.from_pretrained("martingrzzler/clip-word-concreteness")
  • Notebooks
  • Google Colab
  • Kaggle
clip-word-concreteness
254 MB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 3 commits
martingrzzler's picture
martingrzzler
Create README.md
ddbb673 over 3 years ago
  • .gitattributes
    1.48 kB
    initial commit over 3 years ago
  • README.md
    167 Bytes
    Create README.md over 3 years ago
  • config.json
    614 Bytes
    Upload CLIPForRegression (#1) over 3 years ago
  • pytorch_model.bin

    Detected Pickle imports (4)

    • "torch.FloatStorage",
    • "collections.OrderedDict",
    • "torch.LongStorage",
    • "torch._utils._rebuild_tensor_v2"

    What is a pickle import?

    254 MB
    xet
    Upload CLIPForRegression (#1) over 3 years ago