Audio Classification
Transformers
TensorBoard
Safetensors
wav2vec2
Generated from Trainer
Eval Results (legacy)
Instructions to use birgermoell/dysarthria_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use birgermoell/dysarthria_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="birgermoell/dysarthria_classification")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("birgermoell/dysarthria_classification") model = AutoModelForAudioClassification.from_pretrained("birgermoell/dysarthria_classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 78fa42a31ad7600f95b51126e7f0b80aabfc400dca22b019cf17d0afc0542af5
- Size of remote file:
- 4.6 kB
- SHA256:
- 57160dfb71d9178494f0a4adc84a46666a22874d13943856e8e0e8529bb724af
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