Instructions to use bezzam/xcodec2-hf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bezzam/xcodec2-hf with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="bezzam/xcodec2-hf")# Load model directly from transformers import AutoFeatureExtractor, AutoModel extractor = AutoFeatureExtractor.from_pretrained("bezzam/xcodec2-hf") model = AutoModel.from_pretrained("bezzam/xcodec2-hf") - Notebooks
- Google Colab
- Kaggle
File size: 291 Bytes
888e478 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 | {
"feature_extractor_type": "Xcodec2FeatureExtractor",
"feature_size": 80,
"frame_length": 400,
"frame_shift": 160,
"hop_length": 320,
"num_mel_bins": 80,
"padding_side": "right",
"padding_value": 1,
"return_attention_mask": true,
"sampling_rate": 16000,
"stride": 2
}
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