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Aniemore
/
hubert-emotion-russian-resd-quantized

Audio Classification
Transformers
Safetensors
Russian
emotion-recognition
speech-emotion-recognition
speech
russian
quantized
compressed-tensors
int8
fp8
int4
Eval Results (legacy)
Model card Files Files and versions
xet
Community

Instructions to use Aniemore/hubert-emotion-russian-resd-quantized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Aniemore/hubert-emotion-russian-resd-quantized with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("audio-classification", model="Aniemore/hubert-emotion-russian-resd-quantized")
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("Aniemore/hubert-emotion-russian-resd-quantized", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
hubert-emotion-russian-resd-quantized
947 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 5 commits
Ar4ikov's picture
Ar4ikov
Add torchaudio, torchcodec and datasets ways to load the audio
6927243 verified 1 day ago
  • assets
    Show weighted accuracy alongside macro-F1; correct the note on GPU memory 1 day ago
  • fp8
    Add INT8, FP8 and INT4 builds of Aniemore/hubert-emotion-russian-resd 1 day ago
  • int4
    Add INT8, FP8 and INT4 builds of Aniemore/hubert-emotion-russian-resd 1 day ago
  • int8
    Add INT8, FP8 and INT4 builds of Aniemore/hubert-emotion-russian-resd 1 day ago
  • .gitattributes
    1.52 kB
    initial commit 1 day ago
  • README.md
    6.69 kB
    Add torchaudio, torchcodec and datasets ways to load the audio 1 day ago