Instructions to use anderloh/testV5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anderloh/testV5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="anderloh/testV5")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("anderloh/testV5") model = AutoModelForAudioClassification.from_pretrained("anderloh/testV5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3741eca90169b89a46ce7d40b7d45cbe0f233bdbaac3e4f5d82b93433dca0c95
- Size of remote file:
- 4.98 kB
- SHA256:
- badce77d3400a78006caf05b691f60a80ba600f5a8aaa93cdac1c558d44170d9
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