Instructions to use dima806/bird_sounds_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dima806/bird_sounds_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="dima806/bird_sounds_classification")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("dima806/bird_sounds_classification") model = AutoModelForAudioClassification.from_pretrained("dima806/bird_sounds_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9d33fb440d50b2e3e5ed2cb60cd4f988c54ad81ba73cc67ab064eec3a6100b45
- Size of remote file:
- 757 MB
- SHA256:
- ebdbf34637abcc1c2b978bf0711e4d03a2563e70fbce70a522f5140fd0992860
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