Instructions to use anderloh/FinetunedWav2vec5ClassProblemNew with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anderloh/FinetunedWav2vec5ClassProblemNew with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="anderloh/FinetunedWav2vec5ClassProblemNew")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("anderloh/FinetunedWav2vec5ClassProblemNew") model = AutoModelForAudioClassification.from_pretrained("anderloh/FinetunedWav2vec5ClassProblemNew") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e1483ddcf05693d80976ae7424c99d0e7991d5b69e6a26867a444bae8301004b
- Size of remote file:
- 95.9 MB
- SHA256:
- c918fc70557b60472fb809450afa8204f0203463432e29e898d3c30ce950f8c7
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