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:
- b44d3ce6e4f678dd1e519a46f2a5c108702110d5a9884b787a619152bc91aeae
- Size of remote file:
- 14.5 kB
- SHA256:
- 8449c2bd6179ccd1c16c06fd60f03fe7c5c4a889a8bffde62f7c4977300ca5e7
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