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:
- 335d15d30934dca2f83efc2bbf89309a46f436def9c177de517ba16278f54fcc
- Size of remote file:
- 378 MB
- SHA256:
- 11b3ba45b7794aef22048618249f3fd15cb200e469f4caa8e098a5d9781d6abf
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