Feature Extraction
Transformers
Safetensors
wav2vec2
pretraining
bioacoustics
audio
self-supervised-learning
dolphin
bottlenose-dolphin
whistle
openwhistle
Instructions to use dolphinteam/OpenWhistle-BioClust with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dolphinteam/OpenWhistle-BioClust with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="dolphinteam/OpenWhistle-BioClust")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForPreTraining processor = AutoProcessor.from_pretrained("dolphinteam/OpenWhistle-BioClust") model = AutoModelForPreTraining.from_pretrained("dolphinteam/OpenWhistle-BioClust", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 215 Bytes
3f64f7b | 1 2 3 4 5 6 7 8 9 10 | {
"do_normalize": true,
"feature_extractor_type": "Wav2Vec2FeatureExtractor",
"feature_size": 1,
"padding_side": "right",
"padding_value": 0.0,
"return_attention_mask": false,
"sampling_rate": 44100
}
|