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hustcw
/
clap-text

Feature Extraction
Transformers
Safetensors
mpnet
custom_code
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use hustcw/clap-text with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use hustcw/clap-text with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="hustcw/clap-text", trust_remote_code=True)
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("hustcw/clap-text", trust_remote_code=True)
    model = AutoModel.from_pretrained("hustcw/clap-text", trust_remote_code=True)
  • Notebooks
  • Google Colab
  • Kaggle
clap-text
439 MB
Ctrl+K
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  • 1 contributor
History: 9 commits
hustcw's picture
hustcw
Update README.md
3c4bfe1 verified about 2 years ago
  • .gitattributes
    1.52 kB
    initial commit about 2 years ago
  • README.md
    4.42 kB
    Update README.md about 2 years ago
  • clap_modeling.py
    10.2 kB
    update modeling about 2 years ago
  • config.json
    618 Bytes
    add modeling about 2 years ago
  • model.safetensors
    438 MB
    xet
    Upload TextEncoder about 2 years ago
  • special_tokens_map.json
    964 Bytes
    Upload tokenizer about 2 years ago
  • tokenizer.json
    711 kB
    Upload tokenizer about 2 years ago
  • tokenizer_config.json
    1.58 kB
    Upload tokenizer about 2 years ago
  • vocab.txt
    232 kB
    Upload tokenizer about 2 years ago