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xjc1022
/
MELP-Encoder-repro

Feature Extraction
Transformers
Safetensors
melp
ecg
electrocardiogram
custom_code
Model card Files Files and versions
xet
Community

Instructions to use xjc1022/MELP-Encoder-repro with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use xjc1022/MELP-Encoder-repro with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="xjc1022/MELP-Encoder-repro", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("xjc1022/MELP-Encoder-repro", trust_remote_code=True, device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
MELP-Encoder-repro
131 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
xjc1022's picture
xjc1022
Fix the repo id in the usage example
0d5fdc4 verified 10 days ago
  • .gitattributes
    1.52 kB
    initial commit 10 days ago
  • README.md
    2.9 kB
    Fix the repo id in the usage example 10 days ago
  • config.json
    602 Bytes
    MELP ECG encoder from the reproduction run (zero-shot avg 78.40) 10 days ago
  • configuration_MELP_Encoder.py
    1.22 kB
    MELP ECG encoder from the reproduction run (zero-shot avg 78.40) 10 days ago
  • model.safetensors
    131 MB
    xet
    MELP ECG encoder from the reproduction run (zero-shot avg 78.40) 10 days ago
  • modeling_MELP_Encoder.py
    9.4 kB
    MELP ECG encoder from the reproduction run (zero-shot avg 78.40) 10 days ago