Instructions to use dima806/cat_dog_sounds_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dima806/cat_dog_sounds_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="dima806/cat_dog_sounds_classification")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("dima806/cat_dog_sounds_classification") model = AutoModelForAudioClassification.from_pretrained("dima806/cat_dog_sounds_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8e2f70bf88ec70ea330ce4ae5e4a4b1a378d266b5818db37e031f352ad66313f
- Size of remote file:
- 378 MB
- SHA256:
- 96a30b90cfd65630774406e72a3f9a6214f30a4ead495763297b46de140a268f
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