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wltjr1007
/
LEAR

Feature Extraction
Transformers
Safetensors
conditional-unet
custom_code
Model card Files Files and versions
xet
Community

Instructions to use wltjr1007/LEAR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use wltjr1007/LEAR with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="wltjr1007/LEAR", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("wltjr1007/LEAR", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
LEAR
294 MB
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  • 1 contributor
History: 6 commits
wltjr1007's picture
wltjr1007
Upload ConditionalUNet
1aaec4f verified over 1 year ago
  • .gitattributes
    1.52 kB
    initial commit over 1 year ago
  • README.md
    5.17 kB
    Upload ConditionalUNet over 1 year ago
  • config.json
    565 Bytes
    Upload ConditionalUNet over 1 year ago
  • configuration_conditional_unet.py
    304 Bytes
    Upload ConditionalUNet over 1 year ago
  • model.safetensors
    294 MB
    xet
    Upload ConditionalUNet over 1 year ago
  • modeling_conditional_unet.py
    3.79 kB
    Upload ConditionalUNet over 1 year ago
  • preprocessor_config.json
    352 Bytes
    Upload processor over 1 year ago