Instructions to use DBD-research-group/AudioProtoPNet-1-BirdSet-XCL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DBD-research-group/AudioProtoPNet-1-BirdSet-XCL with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="DBD-research-group/AudioProtoPNet-1-BirdSet-XCL", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("DBD-research-group/AudioProtoPNet-1-BirdSet-XCL", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 547 Bytes
7b5f1b2 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | {
"auto_map": {
"AutoFeatureExtractor": "processing_protonet.AudioProtoNetFeatureExtractor"
},
"db_scale": null,
"feature_extractor_type": "AudioProtoNetFeatureExtractor",
"feature_size": 1,
"hop_length": 256,
"mean": -13.369,
"mel_scale": null,
"n_fft": 2048,
"n_mels": 256,
"n_stft": 1025,
"padding_side": "right",
"padding_value": 0.0,
"power": 2.0,
"return_attention_mask": true,
"sampling_rate": 32000,
"spec_transform": null,
"std": 13.162,
"stype": "power",
"top_db": 80
}
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