Instructions to use bezzam/xcodec2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bezzam/xcodec2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="bezzam/xcodec2")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("bezzam/xcodec2", dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "feature_extractor_type": "Xcodec2FeatureExtractor", | |
| "feature_size": 80, | |
| "frame_length": 400, | |
| "frame_length_ms": 25.0, | |
| "frame_shift": 160, | |
| "frame_shift_ms": 10.0, | |
| "hop_length": 320, | |
| "num_mel_bins": 80, | |
| "padding_side": "right", | |
| "padding_value": 1, | |
| "return_attention_mask": true, | |
| "sampling_rate": 16000, | |
| "stride": 2 | |
| } | |