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") - Notebooks
- Google Colab
- Kaggle
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README.md
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metrics:
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- accuracy
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- f1
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See https://www.kaggle.com/code/dima806/bird-species-by-sound-detection for more details.
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metrics:
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- accuracy
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- f1
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base_model:
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- facebook/wav2vec2-base-960h
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See https://www.kaggle.com/code/dima806/bird-species-by-sound-detection for more details.
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