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ALM
/
hubert-large-audioset

Audio Classification
Transformers
PyTorch
hubert
feature-extraction
music
audio
speech
audio-representation-learning
arch-benchmark
general-audio
Model card Files Files and versions
xet
Community
2

Instructions to use ALM/hubert-large-audioset with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use ALM/hubert-large-audioset with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("audio-classification", model="ALM/hubert-large-audioset")
    # Load model directly
    from transformers import AutoProcessor, AutoModel
    
    processor = AutoProcessor.from_pretrained("ALM/hubert-large-audioset")
    model = AutoModel.from_pretrained("ALM/hubert-large-audioset")
  • Notebooks
  • Google Colab
  • Kaggle
hubert-large-audioset
2.52 GB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 8 commits
SFconvertbot's picture
SFconvertbot
Adding `safetensors` variant of this model
7ab0720 verified 4 months ago
  • .gitattributes
    1.52 kB
    initial commit over 2 years ago
  • README.md
    3.76 kB
    Update README.md 5 months ago
  • config.json
    1.78 kB
    Added model over 2 years ago
  • model.safetensors
    1.26 GB
    xet
    Adding `safetensors` variant of this model 4 months ago
  • preprocessor_config.json
    212 Bytes
    Added model over 2 years ago
  • pytorch_model.bin

    Detected Pickle imports (3)

    • "torch._utils._rebuild_tensor_v2",
    • "collections.OrderedDict",
    • "torch.FloatStorage"

    What is a pickle import?

    1.26 GB
    xet
    Added model over 2 years ago