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:
- 079ed1aaf222135979e0fa867849c1792eda5b92a82a9ff190231331cc71c6c7
- Size of remote file:
- 3.57 kB
- SHA256:
- 7cca04528be48253fd10861b3c7948f17c06832a97a80d341f0fe3100f9b9577
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