Instructions to use kamilakesbi/ms_clap with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kamilakesbi/ms_clap with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("kamilakesbi/ms_clap", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 473 Bytes
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"feature_extractor_type": "ClapFeatureExtractor",
"feature_size": 64,
"fft_window_size": 1024,
"frequency_max": 14000,
"frequency_min": 50,
"hop_length": 320,
"max_length_s": 7,
"nb_frequency_bins": 513,
"nb_max_samples": 480000,
"padding": "repeat",
"padding_side": "right",
"padding_value": 0.0,
"processor_class": "MSClapProcessor",
"return_attention_mask": false,
"sampling_rate": 44100,
"top_db": null,
"truncation": "rand_trunc"
}
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