Audio Classification
Transformers
PyTorch
TensorBoard
Safetensors
audio-spectrogram-transformer
Generated from Trainer
Eval Results (legacy)
Instructions to use moonseok/wav2vec_final_output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use moonseok/wav2vec_final_output with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="moonseok/wav2vec_final_output")# pip install -U transformers accelerate # Load model directly from transformers import AutoFeatureExtractor, AutoModelForAudioClassification extractor = AutoFeatureExtractor.from_pretrained("moonseok/wav2vec_final_output") model = AutoModelForAudioClassification.from_pretrained("moonseok/wav2vec_final_output", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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