Instructions to use anton-l/wav2vec2-random-tiny-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anton-l/wav2vec2-random-tiny-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="anton-l/wav2vec2-random-tiny-classifier")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("anton-l/wav2vec2-random-tiny-classifier") model = AutoModelForAudioClassification.from_pretrained("anton-l/wav2vec2-random-tiny-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c1c96f67b3243f49269e424d237245fe208807ea090aa3a740694a733c1dd3d7
- Size of remote file:
- 94.6 kB
- SHA256:
- 9644bc4ac6bc52b76ca7342faa1304a68154f398ad1adf08f6cc5545dfc96198
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