Instructions to use Saads/bird_classification_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Saads/bird_classification_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="Saads/bird_classification_model")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("Saads/bird_classification_model") model = AutoModelForAudioClassification.from_pretrained("Saads/bird_classification_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6b061f4aac00d1fd93698c5b732975d5801a07bc8accb3856372a35e63eddd3f
- Size of remote file:
- 379 MB
- SHA256:
- 83a0a61b2b1ed0044d54fa970a8a3c01e4d3c8510b127e11e47d76458c289b8f
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