Instructions to use MatsRooth/wav2vec2-base_down_on with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MatsRooth/wav2vec2-base_down_on with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="MatsRooth/wav2vec2-base_down_on")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("MatsRooth/wav2vec2-base_down_on") model = AutoModelForAudioClassification.from_pretrained("MatsRooth/wav2vec2-base_down_on") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8d8f3565737616fee635ed6f305bf25163b940cab5c91343a03a420a62f6c392
- Size of remote file:
- 378 MB
- SHA256:
- 136a421b7eb433b8f2d54c3517ed182b0b04a97e2d9c7cc0b18f489efbeca8a3
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