Feature Extraction
Transformers
Safetensors
wav2vec2
bioacoustics
audio
self-supervised-learning
dolphin
bottlenose-dolphin
whistle
openwhistle
Instructions to use OpenWhistleNeurIPS26/OpenWhistle-Wav2Vec2.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenWhistleNeurIPS26/OpenWhistle-Wav2Vec2.0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="OpenWhistleNeurIPS26/OpenWhistle-Wav2Vec2.0")# Load model directly from transformers import AutoProcessor, Wav2vec2ForPreTraining_randommask processor = AutoProcessor.from_pretrained("OpenWhistleNeurIPS26/OpenWhistle-Wav2Vec2.0") model = Wav2vec2ForPreTraining_randommask.from_pretrained("OpenWhistleNeurIPS26/OpenWhistle-Wav2Vec2.0") - Notebooks
- Google Colab
- Kaggle
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