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:
- 4413d14fe54c8bd0c2db3ed764bea273ec2b7957e465df299ace2215ecd9c9d1
- Size of remote file:
- 4.98 kB
- SHA256:
- c8e61b5784e26fd2ba4a1e9b13459cd23e4f0cbfef90398cd9d89f4c292d5ef2
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