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hustcw
/
clap-asm

Feature Extraction
Transformers
Safetensors
roformer
custom_code
Model card Files Files and versions
xet
Community
2

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

  • Libraries
  • Transformers

    How to use hustcw/clap-asm with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="hustcw/clap-asm", trust_remote_code=True)
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("hustcw/clap-asm", trust_remote_code=True)
    model = AutoModel.from_pretrained("hustcw/clap-asm", trust_remote_code=True)
  • Notebooks
  • Google Colab
  • Kaggle
clap-asm
448 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 11 commits
hustcw's picture
hustcw
Update README.md
620f4be 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
    654 Bytes
    add clap modeling about 2 years ago
  • model.safetensors
    446 MB
    xet
    Upload AsmEncoder about 2 years ago
  • special_tokens_map.json
    17.3 kB
    Upload tokenizer about 2 years ago
  • tokenizer.json
    971 kB
    Upload tokenizer about 2 years ago
  • tokenizer_config.json
    194 kB
    add clap modeling about 2 years ago
  • vocab.txt
    257 kB
    Upload tokenizer about 2 years ago