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hpcai-tech
/
vqvae

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

Instructions to use hpcai-tech/vqvae with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use hpcai-tech/vqvae with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="hpcai-tech/vqvae", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("hpcai-tech/vqvae", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
vqvae
88.9 MB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 4 commits
ver217's picture
ver217
[feature] support decode from embeddings
0b09127 over 2 years ago
  • .gitattributes
    1.52 kB
    initial commit over 2 years ago
  • README.md
    450 Bytes
    updated license over 2 years ago
  • _utils.py
    3.58 kB
    updated license over 2 years ago
  • attention.py
    23.3 kB
    updated license over 2 years ago
  • config.json
    371 Bytes
    Upload VQVAE over 2 years ago
  • configuration_vqvae.py
    576 Bytes
    Upload VQVAE over 2 years ago
  • model.safetensors
    88.8 MB
    xet
    Upload VQVAE over 2 years ago
  • modeling_vqvae.py
    12.7 kB
    [feature] support decode from embeddings over 2 years ago